```{python}
# Import needed libraries
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from tensorflow.keras.models import Sequential
from tensorflow.keras.optimizers import Adam
from tensorflow.keras import layers
from copy import deepcopy
import datetime as dt
plt.style.use("fivethirtyeight")
```International US Foreign Currency Exchange Rates Predictor
Blog Post Inspiration and Objectives
In this blog post, I was hoping to investigate using Machine Learning to make a financial prediction system. Initially, I was hoping to imitate the ones used for stock prediction. However, since there were too many tutorials on this topic, I decided to investigate another global, financial factor that governs trade internationally: international currency rates. In the news recently, I have heard rumors of how the international standard of utilizing the US dollar could be compromised with other global powers such as China and India rise in global dominance. Thus, I focused my efforts on analyzing the US currency conversion rates to other countries. With that said, let’s try to analyze this topic with some Machine Learning:
Data Preprocessing - Cleaning and Analytics
First, we will read and display the initial dataset in our file system for this blog post, downloaded from Kaggle. This dataset contains loads of valuable information such as almost every major world power’s international US currency conversion rate.
```{python}
# Reading and displaying the initial dataset
df = pd.read_csv("datasets/foreign_exchange_rates.csv")
df
```| Unnamed: 0 | Time Serie | AUSTRALIA - AUSTRALIAN DOLLAR/US$ | EURO AREA - EURO/US$ | NEW ZEALAND - NEW ZELAND DOLLAR/US$ | UNITED KINGDOM - UNITED KINGDOM POUND/US$ | BRAZIL - REAL/US$ | CANADA - CANADIAN DOLLAR/US$ | CHINA - YUAN/US$ | HONG KONG - HONG KONG DOLLAR/US$ | ... | SINGAPORE - SINGAPORE DOLLAR/US$ | DENMARK - DANISH KRONE/US$ | JAPAN - YEN/US$ | MALAYSIA - RINGGIT/US$ | NORWAY - NORWEGIAN KRONE/US$ | SWEDEN - KRONA/US$ | SRI LANKA - SRI LANKAN RUPEE/US$ | SWITZERLAND - FRANC/US$ | TAIWAN - NEW TAIWAN DOLLAR/US$ | THAILAND - BAHT/US$ | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 2000-01-03 | 1.5172 | 0.9847 | 1.9033 | 0.6146 | 1.805 | 1.4465 | 8.2798 | 7.7765 | ... | 1.6563 | 7.329 | 101.7 | 3.8 | 7.964 | 8.443 | 72.3 | 1.5808 | 31.38 | 36.97 |
| 1 | 1 | 2000-01-04 | 1.5239 | 0.97 | 1.9238 | 0.6109 | 1.8405 | 1.4518 | 8.2799 | 7.7775 | ... | 1.6535 | 7.218 | 103.09 | 3.8 | 7.934 | 8.36 | 72.65 | 1.5565 | 30.6 | 37.13 |
| 2 | 2 | 2000-01-05 | 1.5267 | 0.9676 | 1.9339 | 0.6092 | 1.856 | 1.4518 | 8.2798 | 7.778 | ... | 1.656 | 7.208 | 103.77 | 3.8 | 7.935 | 8.353 | 72.95 | 1.5526 | 30.8 | 37.1 |
| 3 | 3 | 2000-01-06 | 1.5291 | 0.9686 | 1.9436 | 0.607 | 1.84 | 1.4571 | 8.2797 | 7.7785 | ... | 1.6655 | 7.2125 | 105.19 | 3.8 | 7.94 | 8.3675 | 72.95 | 1.554 | 31.75 | 37.62 |
| 4 | 4 | 2000-01-07 | 1.5272 | 0.9714 | 1.938 | 0.6104 | 1.831 | 1.4505 | 8.2794 | 7.7783 | ... | 1.6625 | 7.2285 | 105.17 | 3.8 | 7.966 | 8.415 | 73.15 | 1.5623 | 30.85 | 37.3 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 5212 | 5212 | 2019-12-25 | ND | ND | ND | ND | ND | ND | ND | ND | ... | ND | ND | ND | ND | ND | ND | ND | ND | ND | ND |
| 5213 | 5213 | 2019-12-26 | 1.4411 | 0.9007 | 1.5002 | 0.7688 | 4.0602 | 1.3124 | 6.9949 | 7.788 | ... | 1.354 | 6.7295 | 109.67 | 4.1337 | 8.8799 | 9.4108 | 181.3 | 0.9808 | 30.11 | 30.15 |
| 5214 | 5214 | 2019-12-27 | 1.4331 | 0.8949 | 1.4919 | 0.7639 | 4.0507 | 1.3073 | 6.9954 | 7.7874 | ... | 1.352 | 6.6829 | 109.47 | 4.126 | 8.8291 | 9.3405 | 181.35 | 0.9741 | 30.09 | 30.14 |
| 5215 | 5215 | 2019-12-30 | 1.4278 | 0.8915 | 1.4846 | 0.761 | 4.0152 | 1.3058 | 6.9864 | 7.7857 | ... | 1.3483 | 6.6589 | 108.85 | 4.1053 | 8.7839 | 9.3145 | 181.6 | 0.9677 | 30.04 | 29.94 |
| 5216 | 5216 | 2019-12-31 | 1.4225 | 0.8907 | 1.4826 | 0.7536 | 4.019 | 1.2962 | 6.9618 | 7.7894 | ... | 1.3446 | 6.6554 | 108.67 | 4.0918 | 8.7823 | 9.3425 | 181.3 | 0.9677 | 29.91 | 29.75 |
5217 rows × 24 columns
For clarity on the constraints and parameters of the working datasets, I went to find high-level exploratory statistics on all of the datasets: shape, information about all of the entries, etc.
```{python}
# Determining the shape of the initial dataset
df.shape
```(5217, 24)
```{python}
# Getting a sample of the initial dataset through the seeing the first 10 entries
# completely in the dataset
df.head()
```| Unnamed: 0 | Time Serie | AUSTRALIA - AUSTRALIAN DOLLAR/US$ | EURO AREA - EURO/US$ | NEW ZEALAND - NEW ZELAND DOLLAR/US$ | UNITED KINGDOM - UNITED KINGDOM POUND/US$ | BRAZIL - REAL/US$ | CANADA - CANADIAN DOLLAR/US$ | CHINA - YUAN/US$ | HONG KONG - HONG KONG DOLLAR/US$ | ... | SINGAPORE - SINGAPORE DOLLAR/US$ | DENMARK - DANISH KRONE/US$ | JAPAN - YEN/US$ | MALAYSIA - RINGGIT/US$ | NORWAY - NORWEGIAN KRONE/US$ | SWEDEN - KRONA/US$ | SRI LANKA - SRI LANKAN RUPEE/US$ | SWITZERLAND - FRANC/US$ | TAIWAN - NEW TAIWAN DOLLAR/US$ | THAILAND - BAHT/US$ | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 2000-01-03 | 1.5172 | 0.9847 | 1.9033 | 0.6146 | 1.805 | 1.4465 | 8.2798 | 7.7765 | ... | 1.6563 | 7.329 | 101.7 | 3.8 | 7.964 | 8.443 | 72.3 | 1.5808 | 31.38 | 36.97 |
| 1 | 1 | 2000-01-04 | 1.5239 | 0.97 | 1.9238 | 0.6109 | 1.8405 | 1.4518 | 8.2799 | 7.7775 | ... | 1.6535 | 7.218 | 103.09 | 3.8 | 7.934 | 8.36 | 72.65 | 1.5565 | 30.6 | 37.13 |
| 2 | 2 | 2000-01-05 | 1.5267 | 0.9676 | 1.9339 | 0.6092 | 1.856 | 1.4518 | 8.2798 | 7.778 | ... | 1.656 | 7.208 | 103.77 | 3.8 | 7.935 | 8.353 | 72.95 | 1.5526 | 30.8 | 37.1 |
| 3 | 3 | 2000-01-06 | 1.5291 | 0.9686 | 1.9436 | 0.607 | 1.84 | 1.4571 | 8.2797 | 7.7785 | ... | 1.6655 | 7.2125 | 105.19 | 3.8 | 7.94 | 8.3675 | 72.95 | 1.554 | 31.75 | 37.62 |
| 4 | 4 | 2000-01-07 | 1.5272 | 0.9714 | 1.938 | 0.6104 | 1.831 | 1.4505 | 8.2794 | 7.7783 | ... | 1.6625 | 7.2285 | 105.17 | 3.8 | 7.966 | 8.415 | 73.15 | 1.5623 | 30.85 | 37.3 |
5 rows × 24 columns
```{python}
# Figuring out all of the columns (and their names) available for me to use in the dataset
df.columns
```Index(['Unnamed: 0', 'Time Serie', 'AUSTRALIA - AUSTRALIAN DOLLAR/US$',
'EURO AREA - EURO/US$', 'NEW ZEALAND - NEW ZELAND DOLLAR/US$',
'UNITED KINGDOM - UNITED KINGDOM POUND/US$', 'BRAZIL - REAL/US$',
'CANADA - CANADIAN DOLLAR/US$', 'CHINA - YUAN/US$',
'HONG KONG - HONG KONG DOLLAR/US$', 'INDIA - INDIAN RUPEE/US$',
'KOREA - WON/US$', 'MEXICO - MEXICAN PESO/US$',
'SOUTH AFRICA - RAND/US$', 'SINGAPORE - SINGAPORE DOLLAR/US$',
'DENMARK - DANISH KRONE/US$', 'JAPAN - YEN/US$',
'MALAYSIA - RINGGIT/US$', 'NORWAY - NORWEGIAN KRONE/US$',
'SWEDEN - KRONA/US$', 'SRI LANKA - SRI LANKAN RUPEE/US$',
'SWITZERLAND - FRANC/US$', 'TAIWAN - NEW TAIWAN DOLLAR/US$',
'THAILAND - BAHT/US$'],
dtype='object')
```{python}
# Figuring out the number of duplicated elements in the dataset
# (could be problematic if not resolved)
df.duplicated().sum()
```0
```{python}
# Figuring out the number of 'null'/'NaN' elements in the dataset
# (if NaN filling is needed or not)
(df.isnull().sum() / df.shape[0]) * 100
```Unnamed: 0 0.0
Time Serie 0.0
AUSTRALIA - AUSTRALIAN DOLLAR/US$ 0.0
EURO AREA - EURO/US$ 0.0
NEW ZEALAND - NEW ZELAND DOLLAR/US$ 0.0
UNITED KINGDOM - UNITED KINGDOM POUND/US$ 0.0
BRAZIL - REAL/US$ 0.0
CANADA - CANADIAN DOLLAR/US$ 0.0
CHINA - YUAN/US$ 0.0
HONG KONG - HONG KONG DOLLAR/US$ 0.0
INDIA - INDIAN RUPEE/US$ 0.0
KOREA - WON/US$ 0.0
MEXICO - MEXICAN PESO/US$ 0.0
SOUTH AFRICA - RAND/US$ 0.0
SINGAPORE - SINGAPORE DOLLAR/US$ 0.0
DENMARK - DANISH KRONE/US$ 0.0
JAPAN - YEN/US$ 0.0
MALAYSIA - RINGGIT/US$ 0.0
NORWAY - NORWEGIAN KRONE/US$ 0.0
SWEDEN - KRONA/US$ 0.0
SRI LANKA - SRI LANKAN RUPEE/US$ 0.0
SWITZERLAND - FRANC/US$ 0.0
TAIWAN - NEW TAIWAN DOLLAR/US$ 0.0
THAILAND - BAHT/US$ 0.0
dtype: float64
```{python}
# Getting basic information about the dataset
df.info()
```<class 'pandas.core.frame.DataFrame'>
RangeIndex: 5217 entries, 0 to 5216
Data columns (total 24 columns):
# Column Non-Null Count Dtype
--- ------ -------------- -----
0 Unnamed: 0 5217 non-null int64
1 Time Serie 5217 non-null object
2 AUSTRALIA - AUSTRALIAN DOLLAR/US$ 5217 non-null object
3 EURO AREA - EURO/US$ 5217 non-null object
4 NEW ZEALAND - NEW ZELAND DOLLAR/US$ 5217 non-null object
5 UNITED KINGDOM - UNITED KINGDOM POUND/US$ 5217 non-null object
6 BRAZIL - REAL/US$ 5217 non-null object
7 CANADA - CANADIAN DOLLAR/US$ 5217 non-null object
8 CHINA - YUAN/US$ 5217 non-null object
9 HONG KONG - HONG KONG DOLLAR/US$ 5217 non-null object
10 INDIA - INDIAN RUPEE/US$ 5217 non-null object
11 KOREA - WON/US$ 5217 non-null object
12 MEXICO - MEXICAN PESO/US$ 5217 non-null object
13 SOUTH AFRICA - RAND/US$ 5217 non-null object
14 SINGAPORE - SINGAPORE DOLLAR/US$ 5217 non-null object
15 DENMARK - DANISH KRONE/US$ 5217 non-null object
16 JAPAN - YEN/US$ 5217 non-null object
17 MALAYSIA - RINGGIT/US$ 5217 non-null object
18 NORWAY - NORWEGIAN KRONE/US$ 5217 non-null object
19 SWEDEN - KRONA/US$ 5217 non-null object
20 SRI LANKA - SRI LANKAN RUPEE/US$ 5217 non-null object
21 SWITZERLAND - FRANC/US$ 5217 non-null object
22 TAIWAN - NEW TAIWAN DOLLAR/US$ 5217 non-null object
23 THAILAND - BAHT/US$ 5217 non-null object
dtypes: int64(1), object(23)
memory usage: 978.3+ KB
Additionally, before handing my combined Book dataset over for Machine Learning training and prediction, I need to clean the data prior to the analysis stage: removing duplicates, deleting null/NaN vales, fixing types of columns, filling invalid values with suitable alternatives, etc.
```{python}
# Removing unnecessary/unnamed columns in the dataset
df = df.drop("Unnamed: 0", axis=1)
df
```| Time Serie | AUSTRALIA - AUSTRALIAN DOLLAR/US$ | EURO AREA - EURO/US$ | NEW ZEALAND - NEW ZELAND DOLLAR/US$ | UNITED KINGDOM - UNITED KINGDOM POUND/US$ | BRAZIL - REAL/US$ | CANADA - CANADIAN DOLLAR/US$ | CHINA - YUAN/US$ | HONG KONG - HONG KONG DOLLAR/US$ | INDIA - INDIAN RUPEE/US$ | ... | SINGAPORE - SINGAPORE DOLLAR/US$ | DENMARK - DANISH KRONE/US$ | JAPAN - YEN/US$ | MALAYSIA - RINGGIT/US$ | NORWAY - NORWEGIAN KRONE/US$ | SWEDEN - KRONA/US$ | SRI LANKA - SRI LANKAN RUPEE/US$ | SWITZERLAND - FRANC/US$ | TAIWAN - NEW TAIWAN DOLLAR/US$ | THAILAND - BAHT/US$ | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 2000-01-03 | 1.5172 | 0.9847 | 1.9033 | 0.6146 | 1.805 | 1.4465 | 8.2798 | 7.7765 | 43.55 | ... | 1.6563 | 7.329 | 101.7 | 3.8 | 7.964 | 8.443 | 72.3 | 1.5808 | 31.38 | 36.97 |
| 1 | 2000-01-04 | 1.5239 | 0.97 | 1.9238 | 0.6109 | 1.8405 | 1.4518 | 8.2799 | 7.7775 | 43.55 | ... | 1.6535 | 7.218 | 103.09 | 3.8 | 7.934 | 8.36 | 72.65 | 1.5565 | 30.6 | 37.13 |
| 2 | 2000-01-05 | 1.5267 | 0.9676 | 1.9339 | 0.6092 | 1.856 | 1.4518 | 8.2798 | 7.778 | 43.55 | ... | 1.656 | 7.208 | 103.77 | 3.8 | 7.935 | 8.353 | 72.95 | 1.5526 | 30.8 | 37.1 |
| 3 | 2000-01-06 | 1.5291 | 0.9686 | 1.9436 | 0.607 | 1.84 | 1.4571 | 8.2797 | 7.7785 | 43.55 | ... | 1.6655 | 7.2125 | 105.19 | 3.8 | 7.94 | 8.3675 | 72.95 | 1.554 | 31.75 | 37.62 |
| 4 | 2000-01-07 | 1.5272 | 0.9714 | 1.938 | 0.6104 | 1.831 | 1.4505 | 8.2794 | 7.7783 | 43.55 | ... | 1.6625 | 7.2285 | 105.17 | 3.8 | 7.966 | 8.415 | 73.15 | 1.5623 | 30.85 | 37.3 |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 5212 | 2019-12-25 | ND | ND | ND | ND | ND | ND | ND | ND | ND | ... | ND | ND | ND | ND | ND | ND | ND | ND | ND | ND |
| 5213 | 2019-12-26 | 1.4411 | 0.9007 | 1.5002 | 0.7688 | 4.0602 | 1.3124 | 6.9949 | 7.788 | 71.28 | ... | 1.354 | 6.7295 | 109.67 | 4.1337 | 8.8799 | 9.4108 | 181.3 | 0.9808 | 30.11 | 30.15 |
| 5214 | 2019-12-27 | 1.4331 | 0.8949 | 1.4919 | 0.7639 | 4.0507 | 1.3073 | 6.9954 | 7.7874 | 71.45 | ... | 1.352 | 6.6829 | 109.47 | 4.126 | 8.8291 | 9.3405 | 181.35 | 0.9741 | 30.09 | 30.14 |
| 5215 | 2019-12-30 | 1.4278 | 0.8915 | 1.4846 | 0.761 | 4.0152 | 1.3058 | 6.9864 | 7.7857 | 71.3 | ... | 1.3483 | 6.6589 | 108.85 | 4.1053 | 8.7839 | 9.3145 | 181.6 | 0.9677 | 30.04 | 29.94 |
| 5216 | 2019-12-31 | 1.4225 | 0.8907 | 1.4826 | 0.7536 | 4.019 | 1.2962 | 6.9618 | 7.7894 | 71.36 | ... | 1.3446 | 6.6554 | 108.67 | 4.0918 | 8.7823 | 9.3425 | 181.3 | 0.9677 | 29.91 | 29.75 |
5217 rows × 23 columns
```{python}
# Converting the date column into a string representation to a parsable
# Datetime object (needed for later)
df = df.rename(columns={"Time Serie": "DATE"})
def str_to_datetime(date_str: str):
split = tuple(date_str.split("-"))
year, month, day = int(split[0]), int(split[1]), int(split[2])
return dt.datetime(year, month, day)
df["DATE"] = df["DATE"].apply(str_to_datetime)
df["DATE"]
```0 2000-01-03
1 2000-01-04
2 2000-01-05
3 2000-01-06
4 2000-01-07
...
5212 2019-12-25
5213 2019-12-26
5214 2019-12-27
5215 2019-12-30
5216 2019-12-31
Name: DATE, Length: 5217, dtype: datetime64[ns]
As shown below, I had decided to filter out all of the countries except Austrailia, Canada, the United Kingdom, and Switzerland because those countries had the most stable and consistent international currency rates as well as the most comparable (1:1) currency rates with the United States. One additional reason that these countries were selected for this blog post was do the geographical diversity covered most landmass continents across the world, representative of the global market interactions that the United States deals with on a day-to-day basis.
```{python}
# Making the "Date" column the new index (better identifer/key in dataset)
# Taking out other countries except Austrailia, Canada, UK, and
# Switzerland from dataset for Machine Learning blog post
df.index = df.pop("DATE")
df = df[["AUSTRALIA - AUSTRALIAN DOLLAR/US$",
"CANADA - CANADIAN DOLLAR/US$",
"UNITED KINGDOM - UNITED KINGDOM POUND/US$",
"SWITZERLAND - FRANC/US$"]]
df
```| AUSTRALIA - AUSTRALIAN DOLLAR/US$ | CANADA - CANADIAN DOLLAR/US$ | UNITED KINGDOM - UNITED KINGDOM POUND/US$ | SWITZERLAND - FRANC/US$ | |
|---|---|---|---|---|
| DATE | ||||
| 2000-01-03 | 1.5172 | 1.4465 | 0.6146 | 1.5808 |
| 2000-01-04 | 1.5239 | 1.4518 | 0.6109 | 1.5565 |
| 2000-01-05 | 1.5267 | 1.4518 | 0.6092 | 1.5526 |
| 2000-01-06 | 1.5291 | 1.4571 | 0.607 | 1.554 |
| 2000-01-07 | 1.5272 | 1.4505 | 0.6104 | 1.5623 |
| ... | ... | ... | ... | ... |
| 2019-12-25 | ND | ND | ND | ND |
| 2019-12-26 | 1.4411 | 1.3124 | 0.7688 | 0.9808 |
| 2019-12-27 | 1.4331 | 1.3073 | 0.7639 | 0.9741 |
| 2019-12-30 | 1.4278 | 1.3058 | 0.761 | 0.9677 |
| 2019-12-31 | 1.4225 | 1.2962 | 0.7536 | 0.9677 |
5217 rows × 4 columns
```{python}
# Converting of all numerical international currency rates to 2-decimal
# rates (easier to work with for later)
for col in df:
df[col] = df[col].map(lambda entry: entry if entry == "ND" else round(float(entry), 2))
df
```| AUSTRALIA - AUSTRALIAN DOLLAR/US$ | CANADA - CANADIAN DOLLAR/US$ | UNITED KINGDOM - UNITED KINGDOM POUND/US$ | SWITZERLAND - FRANC/US$ | |
|---|---|---|---|---|
| DATE | ||||
| 2000-01-03 | 1.52 | 1.45 | 0.61 | 1.58 |
| 2000-01-04 | 1.52 | 1.45 | 0.61 | 1.56 |
| 2000-01-05 | 1.53 | 1.45 | 0.61 | 1.55 |
| 2000-01-06 | 1.53 | 1.46 | 0.61 | 1.55 |
| 2000-01-07 | 1.53 | 1.45 | 0.61 | 1.56 |
| ... | ... | ... | ... | ... |
| 2019-12-25 | ND | ND | ND | ND |
| 2019-12-26 | 1.44 | 1.31 | 0.77 | 0.98 |
| 2019-12-27 | 1.43 | 1.31 | 0.76 | 0.97 |
| 2019-12-30 | 1.43 | 1.31 | 0.76 | 0.97 |
| 2019-12-31 | 1.42 | 1.3 | 0.75 | 0.97 |
5217 rows × 4 columns
```{python}
# Removing all of the dated rows that contains "ND" as a way to avoid problems
# when trying to interlay Machine Learning algorithms that require only
# quantitative data with categorical entries
nd_index_list: set[str] = set()
for row_index, _ in df.iterrows():
for col_entry in df.loc[row_index]:
if col_entry == "ND":
nd_index_list.add(row_index)
df = df.drop(labels=list(nd_index_list), axis=0)
df
```| AUSTRALIA - AUSTRALIAN DOLLAR/US$ | CANADA - CANADIAN DOLLAR/US$ | UNITED KINGDOM - UNITED KINGDOM POUND/US$ | SWITZERLAND - FRANC/US$ | |
|---|---|---|---|---|
| DATE | ||||
| 2000-01-03 | 1.52 | 1.45 | 0.61 | 1.58 |
| 2000-01-04 | 1.52 | 1.45 | 0.61 | 1.56 |
| 2000-01-05 | 1.53 | 1.45 | 0.61 | 1.55 |
| 2000-01-06 | 1.53 | 1.46 | 0.61 | 1.55 |
| 2000-01-07 | 1.53 | 1.45 | 0.61 | 1.56 |
| ... | ... | ... | ... | ... |
| 2019-12-24 | 1.44 | 1.32 | 0.77 | 0.98 |
| 2019-12-26 | 1.44 | 1.31 | 0.77 | 0.98 |
| 2019-12-27 | 1.43 | 1.31 | 0.76 | 0.97 |
| 2019-12-30 | 1.43 | 1.31 | 0.76 | 0.97 |
| 2019-12-31 | 1.42 | 1.3 | 0.75 | 0.97 |
5019 rows × 4 columns
As shown in the code snippet below, with some online references, the df_to_windowed_df function describes a way to use prediction values. A new international currency rate dataframe is created which includes the rows encompassing the 3 previous dates prior to the current date of when the international currency rate was reported as well as the current rate that day. This would be helpful for later Machine Learning predictions because the previous 3 dates and the current will provide it enough context to make more insightful predictions on the future of the international currency rates between that respective country specified and the United States. Later, as you will see, the 3 previous days are going to be the input and the current currency rate (Target) will be our output.
```{python}
def df_to_windowed_df(data_frame: pd.DataFrame, first_date_str: str, last_date_str: str, n: int, col_name: str):
first_date = str_to_datetime(first_date_str)
last_date = str_to_datetime(last_date_str)
target_date = first_date
dates: list = []
X: list = []
Y: list = []
last_time = False
while True:
df_subset = data_frame.loc[:target_date].tail(n + 1)
if (len(df_subset) != n + 1):
print("Error: Window of size " + str(n) + " is too large for date " + str(target_date))
return
values = df_subset[col_name].to_numpy()
x, y = values[:-1], values[-1]
dates.append(target_date)
X.append(x)
Y.append(y)
next_week = data_frame.loc[target_date:target_date + dt.timedelta(days=7)]
next_datetime_str = str(next_week.head(2).tail(1).index.values[0])
next_date_str = next_datetime_str.split("T")[0]
year_month_day = next_date_str.split("-")
year, month, day = year_month_day
next_date = dt.datetime(year=int(year), month=int(month), day=int(day))
if last_time:
break
target_date = next_date
if (target_date == last_date):
last_time = True
returned_df = pd.DataFrame({})
returned_df["Target Date"] = dates
X = np.array(X)
for i in range(0, n):
X[:, i]
returned_df["Target-" + str(n - i)] = X[:, i]
returned_df["Target"] = Y
return returned_df
```Thus, with the df_to_windowed_df function created, we created one for every country to later use for Machine Learning model training and eventual predictions of future rates: Austrailia, Canada, the United Kingdom, and Switzerland.
```{python}
# Convert Austrailia's dataframe to a windowed dataframe
windowed_df_austrailia = df_to_windowed_df(data_frame=df,
first_date_str="2000-01-06",
last_date_str="2019-12-31",
n=3,
col_name="AUSTRALIA - AUSTRALIAN DOLLAR/US$")
windowed_df_austrailia
```| Target Date | Target-3 | Target-2 | Target-1 | Target | |
|---|---|---|---|---|---|
| 0 | 2000-01-06 | 1.52 | 1.52 | 1.53 | 1.53 |
| 1 | 2000-01-07 | 1.52 | 1.53 | 1.53 | 1.53 |
| 2 | 2000-01-10 | 1.53 | 1.53 | 1.53 | 1.52 |
| 3 | 2000-01-11 | 1.53 | 1.53 | 1.52 | 1.52 |
| 4 | 2000-01-12 | 1.53 | 1.52 | 1.52 | 1.52 |
| ... | ... | ... | ... | ... | ... |
| 5011 | 2019-12-24 | 1.45 | 1.45 | 1.45 | 1.44 |
| 5012 | 2019-12-26 | 1.45 | 1.45 | 1.44 | 1.44 |
| 5013 | 2019-12-27 | 1.45 | 1.44 | 1.44 | 1.43 |
| 5014 | 2019-12-30 | 1.44 | 1.44 | 1.43 | 1.43 |
| 5015 | 2019-12-31 | 1.44 | 1.43 | 1.43 | 1.42 |
5016 rows × 5 columns
```{python}
# Convert Canada's dataframe to a windowed dataframe
windowed_df_canada = df_to_windowed_df(data_frame=df,
first_date_str="2000-01-06",
last_date_str="2019-12-31",
n=3,
col_name="CANADA - CANADIAN DOLLAR/US$")
windowed_df_canada
```| Target Date | Target-3 | Target-2 | Target-1 | Target | |
|---|---|---|---|---|---|
| 0 | 2000-01-06 | 1.45 | 1.45 | 1.45 | 1.46 |
| 1 | 2000-01-07 | 1.45 | 1.45 | 1.46 | 1.45 |
| 2 | 2000-01-10 | 1.45 | 1.46 | 1.45 | 1.46 |
| 3 | 2000-01-11 | 1.46 | 1.45 | 1.46 | 1.46 |
| 4 | 2000-01-12 | 1.45 | 1.46 | 1.46 | 1.46 |
| ... | ... | ... | ... | ... | ... |
| 5011 | 2019-12-24 | 1.31 | 1.32 | 1.32 | 1.32 |
| 5012 | 2019-12-26 | 1.32 | 1.32 | 1.32 | 1.31 |
| 5013 | 2019-12-27 | 1.32 | 1.32 | 1.31 | 1.31 |
| 5014 | 2019-12-30 | 1.32 | 1.31 | 1.31 | 1.31 |
| 5015 | 2019-12-31 | 1.31 | 1.31 | 1.31 | 1.30 |
5016 rows × 5 columns
```{python}
# Convert United Kingdom's dataframe to a windowed dataframe
windowed_df_united_kingdom = df_to_windowed_df(data_frame=df,
first_date_str="2000-01-06",
last_date_str="2019-12-31",
n=3,
col_name="UNITED KINGDOM - UNITED KINGDOM POUND/US$")
windowed_df_united_kingdom
```| Target Date | Target-3 | Target-2 | Target-1 | Target | |
|---|---|---|---|---|---|
| 0 | 2000-01-06 | 0.61 | 0.61 | 0.61 | 0.61 |
| 1 | 2000-01-07 | 0.61 | 0.61 | 0.61 | 0.61 |
| 2 | 2000-01-10 | 0.61 | 0.61 | 0.61 | 0.61 |
| 3 | 2000-01-11 | 0.61 | 0.61 | 0.61 | 0.61 |
| 4 | 2000-01-12 | 0.61 | 0.61 | 0.61 | 0.61 |
| ... | ... | ... | ... | ... | ... |
| 5011 | 2019-12-24 | 0.77 | 0.77 | 0.77 | 0.77 |
| 5012 | 2019-12-26 | 0.77 | 0.77 | 0.77 | 0.77 |
| 5013 | 2019-12-27 | 0.77 | 0.77 | 0.77 | 0.76 |
| 5014 | 2019-12-30 | 0.77 | 0.77 | 0.76 | 0.76 |
| 5015 | 2019-12-31 | 0.77 | 0.76 | 0.76 | 0.75 |
5016 rows × 5 columns
```{python}
# Convert Switzerland's dataframe to a windowed dataframe
windowed_df_switzerland = df_to_windowed_df(data_frame=df,
first_date_str="2000-01-06",
last_date_str="2019-12-31",
n=3,
col_name="SWITZERLAND - FRANC/US$")
windowed_df_switzerland
```| Target Date | Target-3 | Target-2 | Target-1 | Target | |
|---|---|---|---|---|---|
| 0 | 2000-01-06 | 1.58 | 1.56 | 1.55 | 1.55 |
| 1 | 2000-01-07 | 1.56 | 1.55 | 1.55 | 1.56 |
| 2 | 2000-01-10 | 1.55 | 1.55 | 1.56 | 1.57 |
| 3 | 2000-01-11 | 1.55 | 1.56 | 1.57 | 1.56 |
| 4 | 2000-01-12 | 1.56 | 1.57 | 1.56 | 1.57 |
| ... | ... | ... | ... | ... | ... |
| 5011 | 2019-12-24 | 0.98 | 0.98 | 0.98 | 0.98 |
| 5012 | 2019-12-26 | 0.98 | 0.98 | 0.98 | 0.98 |
| 5013 | 2019-12-27 | 0.98 | 0.98 | 0.98 | 0.97 |
| 5014 | 2019-12-30 | 0.98 | 0.98 | 0.97 | 0.97 |
| 5015 | 2019-12-31 | 0.98 | 0.97 | 0.97 | 0.97 |
5016 rows × 5 columns
As the Machine Learning model that will be used later in this blog post only accepts numpy arrays, we need to extract each of the following quantities from each respective country’s dataframe: the dates as an np.array, the X-values for input as an 3-dimensional np.array, and the Y-values for output as an np.array. Thus, with some online references, our codebase now has a function called windowed_df_to_date_X_y as shown below to account for this needed transformation.
```{python}
def windowed_df_to_date_X_y(windowed_dataframe: pd.DataFrame):
df_as_np = windowed_dataframe.to_numpy()
dates = df_as_np[:, 0]
middle_matrix = df_as_np[:, 1:-1]
X = middle_matrix.reshape((len(dates), middle_matrix.shape[1], 1))
Y = df_as_np[:, -1]
return dates, X.astype(np.float32), Y.astype(np.float32)
dates_austrailia, X_austrailia, y_austrailia = windowed_df_to_date_X_y(windowed_dataframe=windowed_df_austrailia)
dates_canada, X_canada, y_canada = windowed_df_to_date_X_y(windowed_dataframe=windowed_df_canada)
dates_united_kingdom, X_united_kingdom, y_united_kingdom = windowed_df_to_date_X_y(windowed_dataframe=windowed_df_united_kingdom)
dates_switzerland, X_switzerland, y_switzerland = windowed_df_to_date_X_y(windowed_dataframe=windowed_df_switzerland)
print(dates_austrailia.shape, X_austrailia.shape, y_austrailia.shape)
print(dates_canada.shape, X_canada.shape, y_canada.shape)
print(dates_united_kingdom.shape, X_united_kingdom.shape, y_united_kingdom.shape)
print(dates_switzerland.shape, X_switzerland.shape, y_switzerland.shape)
len(windowed_df_austrailia), len(windowed_df_canada), len(windowed_df_united_kingdom), len(windowed_df_switzerland)
```(5016,) (5016, 3, 1) (5016,)
(5016,) (5016, 3, 1) (5016,)
(5016,) (5016, 3, 1) (5016,)
(5016,) (5016, 3, 1) (5016,)
(5016, 5016, 5016, 5016)
Here, I am trying to a visualization of the cleaned dataset before we pass it over for Machine Learning training and prediction. To show the rate of change for the International Currency Rates for Austrailia, Canada, the United Kingdom, and Switzerland over the 20-year period as collected in the data set, I put together a line graph as shown below.
```{python}
# Plotting the each four countries currency rates (per US dollar) from
# 2000 - 2020
plt.plot(df.index, df["AUSTRALIA - AUSTRALIAN DOLLAR/US$"], label="AUS to USD", linewidth=1)
plt.plot(df.index, df[ "CANADA - CANADIAN DOLLAR/US$"], label="CAN to USD", linewidth=1)
plt.plot(df.index, df["UNITED KINGDOM - UNITED KINGDOM POUND/US$"], label="GBR to USD", linewidth=1)
plt.plot(df.index, df["SWITZERLAND - FRANC/US$"], label="CHE to USD", linewidth=1)
plt.legend(loc="upper right")
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date", fontsize=12)
plt.ylabel("Currency Rate of the Respective Country to USD", fontsize=12)
plt.title("Culmination of the All Four Countries' Datasets - After Parsing But Before Machine Learning Alterations")
plt.show()
```Machine Learning - Model Training and Evaluation
Great, now we are onto the Machine Learning part of the blog post!
For this blog post, I worked to create Machine Learning models for each country’s dataset separately. I started with Austrailia’s data first (as shown below):
```{python}
# Getting the location of the 80th and 90th percentile of the number of points
# in the dataset for later train, vailidation, and test category splitting
percentile_80 = int(len(windowed_df_austrailia) * 0.8)
percentile_90 = int(len(windowed_df_austrailia) * 0.9)
percentile_80, percentile_90
```(4012, 4514)
Since the data (date, X, and y) is split into three np.arrays and to be more efficient, I will manually split Austrailia’s data into train, test, and validation datasets for the Machine Learning model with 80% going to the training dataset, the next 10% going to the validation dataset, and the last 10% going to the test dataset for each np.array respectively. This split should be acceptable because I did not mix-and-match training & validation datasets with my testing datasets, wihch would invalidate my entire Machine Learning model. Additionally, looking at the presented in the validation and testing datasets, the range of these respective datasets have been reached before in my training dataset, meaning I anticipated my model should be able to reasonably predict these expected ranges with considerable accuracy.
```{python}
# Splitting Austrailia's data into train, test, and validation sets on 3
# mediums: the X-axis, the y-axis, and the indices (represented by dates)
dates_austrailia_train, X_austrailia_train, y_austrailia_train = dates_austrailia[:percentile_80], X_austrailia[:percentile_80], y_austrailia[:percentile_80]
dates_austrailia_val, X_austrailia_val, y_austrailia_val = dates_austrailia[percentile_80:percentile_90], X_austrailia[percentile_80:percentile_90], y_austrailia[percentile_80:percentile_90]
dates_austrailia_test, X_austrailia_test, y_austrailia_test = dates_austrailia[percentile_90:], X_austrailia[percentile_90:], y_austrailia[percentile_90:]
plt.plot(dates_austrailia_train, y_austrailia_train, linewidth=1)
plt.plot(dates_austrailia_val, y_austrailia_val, linewidth=1)
plt.plot(dates_austrailia_test, y_austrailia_test, linewidth=1)
plt.legend(["Training", "Validation", "Testing"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Split of Austrailia's Data for LSTM Model")
plt.show()
```Now, I began to configure the Machine Learning model. We added Sequential layers: an Input layer 3 by 1 because we will have 3 np.arrays of Input and 1 np.array as output, utilize a LSTM (Long Short-Term Memory) layer of 64 neurons, apply 2 levels of dense layers with 32 neurons and folliowing recommendations online to use the RELU (Rectified Linear Unit) Activiation Function, and I followed up with one last dense layer of 1 neuron as our output layer since we are just trying to linearly-predict the next currency-rate on a near-future date. Once I configured the Sequential layers, we are ready to compile the model, utilzing the mean_square_error as our minimizing loss function, using the Adam optimizer, and comparing our trained model against our data with the mean_absolute_error metric. Lastly, I fitted our model, utilzing our X_train and Y_train datasets for fitting with validation from our X_valid and Y_valid datasets at 100 epochs.
```{python}
# Configuring the Machine Learning Tensorflow Model for Austrailia
austrailia_model = Sequential([layers.Input((3, 1)),
layers.LSTM(64),
layers.Dense(32, activation="relu"),
layers.Dense(32, activation="relu"),
layers.Dense(1)])
austrailia_model.compile(loss="mse",
optimizer=Adam(learning_rate=0.001),
metrics=["mean_absolute_error"])
austrailia_model.fit(X_austrailia_train, y_austrailia_train, validation_data=(X_austrailia_val, y_austrailia_val), epochs=100)
```Epoch 1/100
1/126 [..............................] - ETA: 3:37 - loss: 1.7536 - mean_absolute_error: 1.2952 21/126 [====>.........................] - ETA: 0s - loss: 1.1162 - mean_absolute_error: 1.0100 44/126 [=========>....................] - ETA: 0s - loss: 0.5853 - mean_absolute_error: 0.6193 66/126 [==============>...............] - ETA: 0s - loss: 0.3937 - mean_absolute_error: 0.4392 88/126 [===================>..........] - ETA: 0s - loss: 0.2966 - mean_absolute_error: 0.3450111/126 [=========================>....] - ETA: 0s - loss: 0.2360 - mean_absolute_error: 0.2845126/126 [==============================] - 2s 6ms/step - loss: 0.2093 - mean_absolute_error: 0.2571 - val_loss: 1.6054e-04 - val_mean_absolute_error: 0.0101
Epoch 2/100
1/126 [..............................] - ETA: 0s - loss: 0.0035 - mean_absolute_error: 0.0481 24/126 [====>.........................] - ETA: 0s - loss: 0.0028 - mean_absolute_error: 0.0437 46/126 [=========>....................] - ETA: 0s - loss: 0.0025 - mean_absolute_error: 0.0418 68/126 [===============>..............] - ETA: 0s - loss: 0.0022 - mean_absolute_error: 0.0391 91/126 [====================>.........] - ETA: 0s - loss: 0.0020 - mean_absolute_error: 0.0366113/126 [=========================>....] - ETA: 0s - loss: 0.0018 - mean_absolute_error: 0.0344126/126 [==============================] - 0s 3ms/step - loss: 0.0017 - mean_absolute_error: 0.0332 - val_loss: 1.2231e-04 - val_mean_absolute_error: 0.0086
Epoch 3/100
1/126 [..............................] - ETA: 0s - loss: 6.8839e-04 - mean_absolute_error: 0.0211 23/126 [====>.........................] - ETA: 0s - loss: 5.6958e-04 - mean_absolute_error: 0.0192 46/126 [=========>....................] - ETA: 0s - loss: 5.3205e-04 - mean_absolute_error: 0.0183 67/126 [==============>...............] - ETA: 0s - loss: 4.9201e-04 - mean_absolute_error: 0.0175 88/126 [===================>..........] - ETA: 0s - loss: 4.5517e-04 - mean_absolute_error: 0.0167110/126 [=========================>....] - ETA: 0s - loss: 4.3286e-04 - mean_absolute_error: 0.0161126/126 [==============================] - 0s 3ms/step - loss: 4.1454e-04 - mean_absolute_error: 0.0157 - val_loss: 1.4910e-04 - val_mean_absolute_error: 0.0095
Epoch 4/100
1/126 [..............................] - ETA: 0s - loss: 1.8700e-04 - mean_absolute_error: 0.0116 23/126 [====>.........................] - ETA: 0s - loss: 3.2906e-04 - mean_absolute_error: 0.0132 46/126 [=========>....................] - ETA: 0s - loss: 2.8870e-04 - mean_absolute_error: 0.0126 68/126 [===============>..............] - ETA: 0s - loss: 2.8776e-04 - mean_absolute_error: 0.0125 91/126 [====================>.........] - ETA: 0s - loss: 2.7597e-04 - mean_absolute_error: 0.0123113/126 [=========================>....] - ETA: 0s - loss: 2.7640e-04 - mean_absolute_error: 0.0123126/126 [==============================] - 0s 3ms/step - loss: 2.6825e-04 - mean_absolute_error: 0.0121 - val_loss: 1.5108e-04 - val_mean_absolute_error: 0.0096
Epoch 5/100
1/126 [..............................] - ETA: 0s - loss: 1.5485e-04 - mean_absolute_error: 0.0097 23/126 [====>.........................] - ETA: 0s - loss: 2.5309e-04 - mean_absolute_error: 0.0116 45/126 [=========>....................] - ETA: 0s - loss: 2.5677e-04 - mean_absolute_error: 0.0116 67/126 [==============>...............] - ETA: 0s - loss: 2.6513e-04 - mean_absolute_error: 0.0118 90/126 [====================>.........] - ETA: 0s - loss: 2.6179e-04 - mean_absolute_error: 0.0118113/126 [=========================>....] - ETA: 0s - loss: 2.5722e-04 - mean_absolute_error: 0.0117126/126 [==============================] - 0s 3ms/step - loss: 2.6367e-04 - mean_absolute_error: 0.0118 - val_loss: 1.4980e-04 - val_mean_absolute_error: 0.0096
Epoch 6/100
1/126 [..............................] - ETA: 0s - loss: 2.8081e-04 - mean_absolute_error: 0.0135 22/126 [====>.........................] - ETA: 0s - loss: 2.7708e-04 - mean_absolute_error: 0.0122 35/126 [=======>......................] - ETA: 0s - loss: 2.6291e-04 - mean_absolute_error: 0.0119 54/126 [===========>..................] - ETA: 0s - loss: 2.8262e-04 - mean_absolute_error: 0.0120 76/126 [=================>............] - ETA: 0s - loss: 2.7378e-04 - mean_absolute_error: 0.0119 99/126 [======================>.......] - ETA: 0s - loss: 2.6961e-04 - mean_absolute_error: 0.0118122/126 [============================>.] - ETA: 0s - loss: 2.6818e-04 - mean_absolute_error: 0.0119126/126 [==============================] - 0s 3ms/step - loss: 2.6778e-04 - mean_absolute_error: 0.0119 - val_loss: 1.2298e-04 - val_mean_absolute_error: 0.0087
Epoch 7/100
1/126 [..............................] - ETA: 0s - loss: 7.7710e-04 - mean_absolute_error: 0.0170 23/126 [====>.........................] - ETA: 0s - loss: 2.3855e-04 - mean_absolute_error: 0.0111 45/126 [=========>....................] - ETA: 0s - loss: 2.6045e-04 - mean_absolute_error: 0.0116 67/126 [==============>...............] - ETA: 0s - loss: 2.4925e-04 - mean_absolute_error: 0.0115 90/126 [====================>.........] - ETA: 0s - loss: 2.5305e-04 - mean_absolute_error: 0.0116113/126 [=========================>....] - ETA: 0s - loss: 2.6602e-04 - mean_absolute_error: 0.0118126/126 [==============================] - 0s 3ms/step - loss: 2.6291e-04 - mean_absolute_error: 0.0117 - val_loss: 1.2072e-04 - val_mean_absolute_error: 0.0086
Epoch 8/100
1/126 [..............................] - ETA: 0s - loss: 1.5483e-04 - mean_absolute_error: 0.0089 18/126 [===>..........................] - ETA: 0s - loss: 2.4902e-04 - mean_absolute_error: 0.0116 33/126 [======>.......................] - ETA: 0s - loss: 2.5307e-04 - mean_absolute_error: 0.0115 55/126 [============>.................] - ETA: 0s - loss: 2.6851e-04 - mean_absolute_error: 0.0116 77/126 [=================>............] - ETA: 0s - loss: 2.6948e-04 - mean_absolute_error: 0.0117 98/126 [======================>.......] - ETA: 0s - loss: 2.5601e-04 - mean_absolute_error: 0.0115121/126 [===========================>..] - ETA: 0s - loss: 2.5485e-04 - mean_absolute_error: 0.0116126/126 [==============================] - 0s 3ms/step - loss: 2.5898e-04 - mean_absolute_error: 0.0116 - val_loss: 1.2170e-04 - val_mean_absolute_error: 0.0086
Epoch 9/100
1/126 [..............................] - ETA: 0s - loss: 2.2630e-04 - mean_absolute_error: 0.0115 24/126 [====>.........................] - ETA: 0s - loss: 2.7980e-04 - mean_absolute_error: 0.0120 46/126 [=========>....................] - ETA: 0s - loss: 2.6249e-04 - mean_absolute_error: 0.0117 68/126 [===============>..............] - ETA: 0s - loss: 2.6193e-04 - mean_absolute_error: 0.0117 89/126 [====================>.........] - ETA: 0s - loss: 2.6571e-04 - mean_absolute_error: 0.0117110/126 [=========================>....] - ETA: 0s - loss: 2.7204e-04 - mean_absolute_error: 0.0119126/126 [==============================] - 0s 3ms/step - loss: 2.6602e-04 - mean_absolute_error: 0.0118 - val_loss: 1.2155e-04 - val_mean_absolute_error: 0.0086
Epoch 10/100
1/126 [..............................] - ETA: 0s - loss: 1.8352e-04 - mean_absolute_error: 0.0113 15/126 [==>...........................] - ETA: 0s - loss: 2.0576e-04 - mean_absolute_error: 0.0112 36/126 [=======>......................] - ETA: 0s - loss: 2.5220e-04 - mean_absolute_error: 0.0116 60/126 [=============>................] - ETA: 0s - loss: 2.5219e-04 - mean_absolute_error: 0.0116 82/126 [==================>...........] - ETA: 0s - loss: 2.4516e-04 - mean_absolute_error: 0.0115104/126 [=======================>......] - ETA: 0s - loss: 2.5153e-04 - mean_absolute_error: 0.0116126/126 [==============================] - 0s 3ms/step - loss: 2.5671e-04 - mean_absolute_error: 0.0117 - val_loss: 1.4643e-04 - val_mean_absolute_error: 0.0098
Epoch 11/100
1/126 [..............................] - ETA: 0s - loss: 2.6912e-04 - mean_absolute_error: 0.0133 23/126 [====>.........................] - ETA: 0s - loss: 3.1709e-04 - mean_absolute_error: 0.0129 44/126 [=========>....................] - ETA: 0s - loss: 2.8045e-04 - mean_absolute_error: 0.0121 66/126 [==============>...............] - ETA: 0s - loss: 2.9848e-04 - mean_absolute_error: 0.0124 86/126 [===================>..........] - ETA: 0s - loss: 2.7852e-04 - mean_absolute_error: 0.0120106/126 [========================>.....] - ETA: 0s - loss: 2.6888e-04 - mean_absolute_error: 0.0119126/126 [==============================] - ETA: 0s - loss: 2.6743e-04 - mean_absolute_error: 0.0119126/126 [==============================] - 0s 3ms/step - loss: 2.6743e-04 - mean_absolute_error: 0.0119 - val_loss: 1.5739e-04 - val_mean_absolute_error: 0.0098
Epoch 12/100
1/126 [..............................] - ETA: 0s - loss: 7.6784e-04 - mean_absolute_error: 0.0126 21/126 [====>.........................] - ETA: 0s - loss: 2.9609e-04 - mean_absolute_error: 0.0120 41/126 [========>.....................] - ETA: 0s - loss: 2.5901e-04 - mean_absolute_error: 0.0116 61/126 [=============>................] - ETA: 0s - loss: 2.5555e-04 - mean_absolute_error: 0.0116 80/126 [==================>...........] - ETA: 0s - loss: 2.5444e-04 - mean_absolute_error: 0.0116 99/126 [======================>.......] - ETA: 0s - loss: 2.5849e-04 - mean_absolute_error: 0.0116119/126 [===========================>..] - ETA: 0s - loss: 2.5175e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.5649e-04 - mean_absolute_error: 0.0116 - val_loss: 1.7536e-04 - val_mean_absolute_error: 0.0104
Epoch 13/100
1/126 [..............................] - ETA: 0s - loss: 1.9098e-04 - mean_absolute_error: 0.0109 21/126 [====>.........................] - ETA: 0s - loss: 2.5221e-04 - mean_absolute_error: 0.0116 41/126 [========>.....................] - ETA: 0s - loss: 2.3442e-04 - mean_absolute_error: 0.0113 61/126 [=============>................] - ETA: 0s - loss: 2.5298e-04 - mean_absolute_error: 0.0116 81/126 [==================>...........] - ETA: 0s - loss: 2.5003e-04 - mean_absolute_error: 0.0116101/126 [=======================>......] - ETA: 0s - loss: 2.6935e-04 - mean_absolute_error: 0.0118121/126 [===========================>..] - ETA: 0s - loss: 2.6595e-04 - mean_absolute_error: 0.0118126/126 [==============================] - 0s 3ms/step - loss: 2.6427e-04 - mean_absolute_error: 0.0118 - val_loss: 1.2119e-04 - val_mean_absolute_error: 0.0086
Epoch 14/100
1/126 [..............................] - ETA: 0s - loss: 2.4968e-04 - mean_absolute_error: 0.0130 20/126 [===>..........................] - ETA: 0s - loss: 2.2839e-04 - mean_absolute_error: 0.0114 40/126 [========>.....................] - ETA: 0s - loss: 2.4595e-04 - mean_absolute_error: 0.0115 60/126 [=============>................] - ETA: 0s - loss: 2.4369e-04 - mean_absolute_error: 0.0114 80/126 [==================>...........] - ETA: 0s - loss: 2.6672e-04 - mean_absolute_error: 0.0118100/126 [======================>.......] - ETA: 0s - loss: 2.6683e-04 - mean_absolute_error: 0.0118120/126 [===========================>..] - ETA: 0s - loss: 2.6351e-04 - mean_absolute_error: 0.0117126/126 [==============================] - 0s 3ms/step - loss: 2.6115e-04 - mean_absolute_error: 0.0117 - val_loss: 1.1999e-04 - val_mean_absolute_error: 0.0085
Epoch 15/100
1/126 [..............................] - ETA: 0s - loss: 1.3807e-04 - mean_absolute_error: 0.0100 22/126 [====>.........................] - ETA: 0s - loss: 3.3496e-04 - mean_absolute_error: 0.0122 43/126 [=========>....................] - ETA: 0s - loss: 2.7093e-04 - mean_absolute_error: 0.0116 62/126 [=============>................] - ETA: 0s - loss: 2.6057e-04 - mean_absolute_error: 0.0116 82/126 [==================>...........] - ETA: 0s - loss: 2.5578e-04 - mean_absolute_error: 0.0115101/126 [=======================>......] - ETA: 0s - loss: 2.4389e-04 - mean_absolute_error: 0.0113120/126 [===========================>..] - ETA: 0s - loss: 2.5054e-04 - mean_absolute_error: 0.0114126/126 [==============================] - 0s 3ms/step - loss: 2.5163e-04 - mean_absolute_error: 0.0114 - val_loss: 1.3413e-04 - val_mean_absolute_error: 0.0090
Epoch 16/100
1/126 [..............................] - ETA: 0s - loss: 2.3846e-04 - mean_absolute_error: 0.0133 22/126 [====>.........................] - ETA: 0s - loss: 2.6862e-04 - mean_absolute_error: 0.0117 42/126 [=========>....................] - ETA: 0s - loss: 2.7396e-04 - mean_absolute_error: 0.0115 62/126 [=============>................] - ETA: 0s - loss: 2.5671e-04 - mean_absolute_error: 0.0114 82/126 [==================>...........] - ETA: 0s - loss: 2.5250e-04 - mean_absolute_error: 0.0115 99/126 [======================>.......] - ETA: 0s - loss: 2.4926e-04 - mean_absolute_error: 0.0115112/126 [=========================>....] - ETA: 0s - loss: 2.5310e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.5241e-04 - mean_absolute_error: 0.0115 - val_loss: 1.2024e-04 - val_mean_absolute_error: 0.0086
Epoch 17/100
1/126 [..............................] - ETA: 0s - loss: 2.3215e-04 - mean_absolute_error: 0.0116 20/126 [===>..........................] - ETA: 0s - loss: 2.8104e-04 - mean_absolute_error: 0.0118 39/126 [========>.....................] - ETA: 0s - loss: 2.7026e-04 - mean_absolute_error: 0.0121 59/126 [=============>................] - ETA: 0s - loss: 2.8696e-04 - mean_absolute_error: 0.0121 79/126 [=================>............] - ETA: 0s - loss: 2.8081e-04 - mean_absolute_error: 0.0120 99/126 [======================>.......] - ETA: 0s - loss: 2.6848e-04 - mean_absolute_error: 0.0117119/126 [===========================>..] - ETA: 0s - loss: 2.6246e-04 - mean_absolute_error: 0.0117126/126 [==============================] - 0s 3ms/step - loss: 2.6163e-04 - mean_absolute_error: 0.0117 - val_loss: 1.6688e-04 - val_mean_absolute_error: 0.0101
Epoch 18/100
1/126 [..............................] - ETA: 0s - loss: 2.3690e-04 - mean_absolute_error: 0.0110 21/126 [====>.........................] - ETA: 0s - loss: 2.7222e-04 - mean_absolute_error: 0.0112 41/126 [========>.....................] - ETA: 0s - loss: 2.7429e-04 - mean_absolute_error: 0.0115 57/126 [============>.................] - ETA: 0s - loss: 2.6810e-04 - mean_absolute_error: 0.0115 69/126 [===============>..............] - ETA: 0s - loss: 2.7199e-04 - mean_absolute_error: 0.0117 88/126 [===================>..........] - ETA: 0s - loss: 2.6636e-04 - mean_absolute_error: 0.0116107/126 [========================>.....] - ETA: 0s - loss: 2.5787e-04 - mean_absolute_error: 0.0115126/126 [==============================] - ETA: 0s - loss: 2.5469e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.5469e-04 - mean_absolute_error: 0.0115 - val_loss: 1.4482e-04 - val_mean_absolute_error: 0.0097
Epoch 19/100
1/126 [..............................] - ETA: 0s - loss: 2.4272e-04 - mean_absolute_error: 0.0135 21/126 [====>.........................] - ETA: 0s - loss: 2.5234e-04 - mean_absolute_error: 0.0123 41/126 [========>.....................] - ETA: 0s - loss: 2.5034e-04 - mean_absolute_error: 0.0118 61/126 [=============>................] - ETA: 0s - loss: 2.5503e-04 - mean_absolute_error: 0.0118 81/126 [==================>...........] - ETA: 0s - loss: 2.8567e-04 - mean_absolute_error: 0.0122101/126 [=======================>......] - ETA: 0s - loss: 2.8289e-04 - mean_absolute_error: 0.0120121/126 [===========================>..] - ETA: 0s - loss: 2.6965e-04 - mean_absolute_error: 0.0119126/126 [==============================] - 0s 3ms/step - loss: 2.6703e-04 - mean_absolute_error: 0.0118 - val_loss: 1.3337e-04 - val_mean_absolute_error: 0.0090
Epoch 20/100
1/126 [..............................] - ETA: 0s - loss: 2.1512e-04 - mean_absolute_error: 0.0109 16/126 [==>...........................] - ETA: 0s - loss: 2.7084e-04 - mean_absolute_error: 0.0118 31/126 [======>.......................] - ETA: 0s - loss: 2.5751e-04 - mean_absolute_error: 0.0115 49/126 [==========>...................] - ETA: 0s - loss: 2.4463e-04 - mean_absolute_error: 0.0113 67/126 [==============>...............] - ETA: 0s - loss: 2.4007e-04 - mean_absolute_error: 0.0111 86/126 [===================>..........] - ETA: 0s - loss: 2.4223e-04 - mean_absolute_error: 0.0113105/126 [========================>.....] - ETA: 0s - loss: 2.5044e-04 - mean_absolute_error: 0.0115124/126 [============================>.] - ETA: 0s - loss: 2.5448e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.5503e-04 - mean_absolute_error: 0.0116 - val_loss: 1.2139e-04 - val_mean_absolute_error: 0.0086
Epoch 21/100
1/126 [..............................] - ETA: 0s - loss: 2.1129e-04 - mean_absolute_error: 0.0103 21/126 [====>.........................] - ETA: 0s - loss: 2.3860e-04 - mean_absolute_error: 0.0114 41/126 [========>.....................] - ETA: 0s - loss: 2.8552e-04 - mean_absolute_error: 0.0120 61/126 [=============>................] - ETA: 0s - loss: 2.8301e-04 - mean_absolute_error: 0.0119 81/126 [==================>...........] - ETA: 0s - loss: 2.7176e-04 - mean_absolute_error: 0.0117101/126 [=======================>......] - ETA: 0s - loss: 2.6318e-04 - mean_absolute_error: 0.0117121/126 [===========================>..] - ETA: 0s - loss: 2.5934e-04 - mean_absolute_error: 0.0117126/126 [==============================] - 0s 3ms/step - loss: 2.5673e-04 - mean_absolute_error: 0.0116 - val_loss: 1.2545e-04 - val_mean_absolute_error: 0.0087
Epoch 22/100
1/126 [..............................] - ETA: 0s - loss: 4.0328e-04 - mean_absolute_error: 0.0139 22/126 [====>.........................] - ETA: 0s - loss: 2.2869e-04 - mean_absolute_error: 0.0114 43/126 [=========>....................] - ETA: 0s - loss: 2.3343e-04 - mean_absolute_error: 0.0112 63/126 [==============>...............] - ETA: 0s - loss: 2.4954e-04 - mean_absolute_error: 0.0113 83/126 [==================>...........] - ETA: 0s - loss: 2.4450e-04 - mean_absolute_error: 0.0113103/126 [=======================>......] - ETA: 0s - loss: 2.4704e-04 - mean_absolute_error: 0.0114122/126 [============================>.] - ETA: 0s - loss: 2.4422e-04 - mean_absolute_error: 0.0114126/126 [==============================] - 0s 3ms/step - loss: 2.5302e-04 - mean_absolute_error: 0.0115 - val_loss: 1.4134e-04 - val_mean_absolute_error: 0.0096
Epoch 23/100
1/126 [..............................] - ETA: 0s - loss: 1.8840e-04 - mean_absolute_error: 0.0112 21/126 [====>.........................] - ETA: 0s - loss: 2.2692e-04 - mean_absolute_error: 0.0112 41/126 [========>.....................] - ETA: 0s - loss: 2.7980e-04 - mean_absolute_error: 0.0118 61/126 [=============>................] - ETA: 0s - loss: 2.7300e-04 - mean_absolute_error: 0.0120 81/126 [==================>...........] - ETA: 0s - loss: 2.6322e-04 - mean_absolute_error: 0.0119101/126 [=======================>......] - ETA: 0s - loss: 2.6529e-04 - mean_absolute_error: 0.0119121/126 [===========================>..] - ETA: 0s - loss: 2.6993e-04 - mean_absolute_error: 0.0120126/126 [==============================] - 0s 3ms/step - loss: 2.6746e-04 - mean_absolute_error: 0.0119 - val_loss: 1.2518e-04 - val_mean_absolute_error: 0.0087
Epoch 24/100
1/126 [..............................] - ETA: 0s - loss: 9.9589e-05 - mean_absolute_error: 0.0082 22/126 [====>.........................] - ETA: 0s - loss: 2.2603e-04 - mean_absolute_error: 0.0111 42/126 [=========>....................] - ETA: 0s - loss: 2.6909e-04 - mean_absolute_error: 0.0115 62/126 [=============>................] - ETA: 0s - loss: 2.5605e-04 - mean_absolute_error: 0.0115 82/126 [==================>...........] - ETA: 0s - loss: 2.6567e-04 - mean_absolute_error: 0.0118102/126 [=======================>......] - ETA: 0s - loss: 2.6468e-04 - mean_absolute_error: 0.0117122/126 [============================>.] - ETA: 0s - loss: 2.5637e-04 - mean_absolute_error: 0.0116126/126 [==============================] - 0s 3ms/step - loss: 2.5512e-04 - mean_absolute_error: 0.0116 - val_loss: 1.2047e-04 - val_mean_absolute_error: 0.0087
Epoch 25/100
1/126 [..............................] - ETA: 0s - loss: 6.9919e-04 - mean_absolute_error: 0.0176 22/126 [====>.........................] - ETA: 0s - loss: 2.6877e-04 - mean_absolute_error: 0.0122 42/126 [=========>....................] - ETA: 0s - loss: 3.0495e-04 - mean_absolute_error: 0.0122 62/126 [=============>................] - ETA: 0s - loss: 2.9283e-04 - mean_absolute_error: 0.0122 82/126 [==================>...........] - ETA: 0s - loss: 2.8173e-04 - mean_absolute_error: 0.0121101/126 [=======================>......] - ETA: 0s - loss: 2.7046e-04 - mean_absolute_error: 0.0119120/126 [===========================>..] - ETA: 0s - loss: 2.5942e-04 - mean_absolute_error: 0.0117126/126 [==============================] - 0s 3ms/step - loss: 2.5873e-04 - mean_absolute_error: 0.0117 - val_loss: 1.2909e-04 - val_mean_absolute_error: 0.0091
Epoch 26/100
1/126 [..............................] - ETA: 0s - loss: 2.9025e-04 - mean_absolute_error: 0.0125 21/126 [====>.........................] - ETA: 0s - loss: 2.8592e-04 - mean_absolute_error: 0.0124 42/126 [=========>....................] - ETA: 0s - loss: 2.5877e-04 - mean_absolute_error: 0.0120 63/126 [==============>...............] - ETA: 0s - loss: 2.8245e-04 - mean_absolute_error: 0.0125 84/126 [===================>..........] - ETA: 0s - loss: 2.8263e-04 - mean_absolute_error: 0.0124104/126 [=======================>......] - ETA: 0s - loss: 2.7074e-04 - mean_absolute_error: 0.0121124/126 [============================>.] - ETA: 0s - loss: 2.7707e-04 - mean_absolute_error: 0.0121126/126 [==============================] - 0s 3ms/step - loss: 2.7602e-04 - mean_absolute_error: 0.0121 - val_loss: 1.2145e-04 - val_mean_absolute_error: 0.0087
Epoch 27/100
1/126 [..............................] - ETA: 0s - loss: 1.5246e-04 - mean_absolute_error: 0.0107 22/126 [====>.........................] - ETA: 0s - loss: 2.6882e-04 - mean_absolute_error: 0.0118 42/126 [=========>....................] - ETA: 0s - loss: 3.0453e-04 - mean_absolute_error: 0.0126 63/126 [==============>...............] - ETA: 0s - loss: 2.7127e-04 - mean_absolute_error: 0.0121 82/126 [==================>...........] - ETA: 0s - loss: 2.6431e-04 - mean_absolute_error: 0.0118102/126 [=======================>......] - ETA: 0s - loss: 2.6329e-04 - mean_absolute_error: 0.0117122/126 [============================>.] - ETA: 0s - loss: 2.6064e-04 - mean_absolute_error: 0.0117126/126 [==============================] - 0s 3ms/step - loss: 2.5780e-04 - mean_absolute_error: 0.0116 - val_loss: 1.3657e-04 - val_mean_absolute_error: 0.0091
Epoch 28/100
1/126 [..............................] - ETA: 0s - loss: 1.9390e-04 - mean_absolute_error: 0.0107 21/126 [====>.........................] - ETA: 0s - loss: 2.0104e-04 - mean_absolute_error: 0.0106 42/126 [=========>....................] - ETA: 0s - loss: 2.1584e-04 - mean_absolute_error: 0.0109 62/126 [=============>................] - ETA: 0s - loss: 2.5397e-04 - mean_absolute_error: 0.0115 81/126 [==================>...........] - ETA: 0s - loss: 2.5373e-04 - mean_absolute_error: 0.0116101/126 [=======================>......] - ETA: 0s - loss: 2.6041e-04 - mean_absolute_error: 0.0116120/126 [===========================>..] - ETA: 0s - loss: 2.6545e-04 - mean_absolute_error: 0.0118126/126 [==============================] - 0s 3ms/step - loss: 2.6959e-04 - mean_absolute_error: 0.0119 - val_loss: 1.1816e-04 - val_mean_absolute_error: 0.0085
Epoch 29/100
1/126 [..............................] - ETA: 0s - loss: 3.3495e-04 - mean_absolute_error: 0.0126 22/126 [====>.........................] - ETA: 0s - loss: 2.7831e-04 - mean_absolute_error: 0.0123 43/126 [=========>....................] - ETA: 0s - loss: 2.5691e-04 - mean_absolute_error: 0.0118 64/126 [==============>...............] - ETA: 0s - loss: 2.5044e-04 - mean_absolute_error: 0.0118 84/126 [===================>..........] - ETA: 0s - loss: 2.4600e-04 - mean_absolute_error: 0.0116103/126 [=======================>......] - ETA: 0s - loss: 2.5262e-04 - mean_absolute_error: 0.0116123/126 [============================>.] - ETA: 0s - loss: 2.5799e-04 - mean_absolute_error: 0.0116126/126 [==============================] - 0s 3ms/step - loss: 2.5672e-04 - mean_absolute_error: 0.0116 - val_loss: 1.1782e-04 - val_mean_absolute_error: 0.0085
Epoch 30/100
1/126 [..............................] - ETA: 0s - loss: 1.5873e-04 - mean_absolute_error: 0.0104 21/126 [====>.........................] - ETA: 0s - loss: 2.4395e-04 - mean_absolute_error: 0.0116 41/126 [========>.....................] - ETA: 0s - loss: 2.6909e-04 - mean_absolute_error: 0.0123 61/126 [=============>................] - ETA: 0s - loss: 2.4893e-04 - mean_absolute_error: 0.0118 81/126 [==================>...........] - ETA: 0s - loss: 2.6675e-04 - mean_absolute_error: 0.0121100/126 [======================>.......] - ETA: 0s - loss: 2.7738e-04 - mean_absolute_error: 0.0122120/126 [===========================>..] - ETA: 0s - loss: 2.7168e-04 - mean_absolute_error: 0.0120126/126 [==============================] - 0s 3ms/step - loss: 2.6859e-04 - mean_absolute_error: 0.0119 - val_loss: 1.2384e-04 - val_mean_absolute_error: 0.0086
Epoch 31/100
1/126 [..............................] - ETA: 0s - loss: 1.1454e-04 - mean_absolute_error: 0.0092 22/126 [====>.........................] - ETA: 0s - loss: 1.9314e-04 - mean_absolute_error: 0.0107 42/126 [=========>....................] - ETA: 0s - loss: 2.2557e-04 - mean_absolute_error: 0.0109 62/126 [=============>................] - ETA: 0s - loss: 2.3906e-04 - mean_absolute_error: 0.0112 82/126 [==================>...........] - ETA: 0s - loss: 2.3216e-04 - mean_absolute_error: 0.0111102/126 [=======================>......] - ETA: 0s - loss: 2.3576e-04 - mean_absolute_error: 0.0112121/126 [===========================>..] - ETA: 0s - loss: 2.5098e-04 - mean_absolute_error: 0.0114126/126 [==============================] - 0s 3ms/step - loss: 2.4820e-04 - mean_absolute_error: 0.0114 - val_loss: 1.5833e-04 - val_mean_absolute_error: 0.0098
Epoch 32/100
1/126 [..............................] - ETA: 0s - loss: 1.6513e-04 - mean_absolute_error: 0.0103 21/126 [====>.........................] - ETA: 0s - loss: 2.4872e-04 - mean_absolute_error: 0.0111 41/126 [========>.....................] - ETA: 0s - loss: 2.6415e-04 - mean_absolute_error: 0.0114 62/126 [=============>................] - ETA: 0s - loss: 2.5705e-04 - mean_absolute_error: 0.0114 82/126 [==================>...........] - ETA: 0s - loss: 2.5397e-04 - mean_absolute_error: 0.0114102/126 [=======================>......] - ETA: 0s - loss: 2.5357e-04 - mean_absolute_error: 0.0115122/126 [============================>.] - ETA: 0s - loss: 2.5375e-04 - mean_absolute_error: 0.0114126/126 [==============================] - 0s 3ms/step - loss: 2.5144e-04 - mean_absolute_error: 0.0114 - val_loss: 1.4254e-04 - val_mean_absolute_error: 0.0093
Epoch 33/100
1/126 [..............................] - ETA: 0s - loss: 7.3674e-05 - mean_absolute_error: 0.0069 21/126 [====>.........................] - ETA: 0s - loss: 2.9123e-04 - mean_absolute_error: 0.0127 42/126 [=========>....................] - ETA: 0s - loss: 2.9636e-04 - mean_absolute_error: 0.0128 62/126 [=============>................] - ETA: 0s - loss: 2.8022e-04 - mean_absolute_error: 0.0125 82/126 [==================>...........] - ETA: 0s - loss: 2.8712e-04 - mean_absolute_error: 0.0126102/126 [=======================>......] - ETA: 0s - loss: 2.8519e-04 - mean_absolute_error: 0.0125122/126 [============================>.] - ETA: 0s - loss: 2.8573e-04 - mean_absolute_error: 0.0124126/126 [==============================] - 0s 3ms/step - loss: 2.8342e-04 - mean_absolute_error: 0.0123 - val_loss: 1.2506e-04 - val_mean_absolute_error: 0.0089
Epoch 34/100
1/126 [..............................] - ETA: 0s - loss: 2.1321e-04 - mean_absolute_error: 0.0118 22/126 [====>.........................] - ETA: 0s - loss: 2.2814e-04 - mean_absolute_error: 0.0114 42/126 [=========>....................] - ETA: 0s - loss: 2.2528e-04 - mean_absolute_error: 0.0109 62/126 [=============>................] - ETA: 0s - loss: 2.6366e-04 - mean_absolute_error: 0.0116 82/126 [==================>...........] - ETA: 0s - loss: 2.6070e-04 - mean_absolute_error: 0.0115102/126 [=======================>......] - ETA: 0s - loss: 2.5782e-04 - mean_absolute_error: 0.0115122/126 [============================>.] - ETA: 0s - loss: 2.5649e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.5442e-04 - mean_absolute_error: 0.0115 - val_loss: 2.0178e-04 - val_mean_absolute_error: 0.0117
Epoch 35/100
1/126 [..............................] - ETA: 0s - loss: 3.4368e-04 - mean_absolute_error: 0.0144 22/126 [====>.........................] - ETA: 0s - loss: 3.1964e-04 - mean_absolute_error: 0.0130 43/126 [=========>....................] - ETA: 0s - loss: 3.3117e-04 - mean_absolute_error: 0.0133 64/126 [==============>...............] - ETA: 0s - loss: 3.0252e-04 - mean_absolute_error: 0.0129 84/126 [===================>..........] - ETA: 0s - loss: 3.0174e-04 - mean_absolute_error: 0.0126104/126 [=======================>......] - ETA: 0s - loss: 2.8899e-04 - mean_absolute_error: 0.0125124/126 [============================>.] - ETA: 0s - loss: 2.8295e-04 - mean_absolute_error: 0.0123126/126 [==============================] - 0s 3ms/step - loss: 2.8164e-04 - mean_absolute_error: 0.0123 - val_loss: 1.1669e-04 - val_mean_absolute_error: 0.0084
Epoch 36/100
1/126 [..............................] - ETA: 0s - loss: 1.8489e-04 - mean_absolute_error: 0.0092 21/126 [====>.........................] - ETA: 0s - loss: 2.7814e-04 - mean_absolute_error: 0.0117 41/126 [========>.....................] - ETA: 0s - loss: 2.3853e-04 - mean_absolute_error: 0.0112 61/126 [=============>................] - ETA: 0s - loss: 2.3818e-04 - mean_absolute_error: 0.0110 80/126 [==================>...........] - ETA: 0s - loss: 2.3154e-04 - mean_absolute_error: 0.0109100/126 [======================>.......] - ETA: 0s - loss: 2.3676e-04 - mean_absolute_error: 0.0111120/126 [===========================>..] - ETA: 0s - loss: 2.4452e-04 - mean_absolute_error: 0.0113126/126 [==============================] - 0s 3ms/step - loss: 2.4205e-04 - mean_absolute_error: 0.0112 - val_loss: 1.1718e-04 - val_mean_absolute_error: 0.0085
Epoch 37/100
1/126 [..............................] - ETA: 0s - loss: 2.4394e-04 - mean_absolute_error: 0.0108 21/126 [====>.........................] - ETA: 0s - loss: 2.1818e-04 - mean_absolute_error: 0.0114 42/126 [=========>....................] - ETA: 0s - loss: 2.5226e-04 - mean_absolute_error: 0.0118 62/126 [=============>................] - ETA: 0s - loss: 2.7585e-04 - mean_absolute_error: 0.0122 83/126 [==================>...........] - ETA: 0s - loss: 2.6779e-04 - mean_absolute_error: 0.0120103/126 [=======================>......] - ETA: 0s - loss: 2.6021e-04 - mean_absolute_error: 0.0118123/126 [============================>.] - ETA: 0s - loss: 2.6467e-04 - mean_absolute_error: 0.0118126/126 [==============================] - 0s 3ms/step - loss: 2.6262e-04 - mean_absolute_error: 0.0118 - val_loss: 1.2046e-04 - val_mean_absolute_error: 0.0085
Epoch 38/100
1/126 [..............................] - ETA: 0s - loss: 1.3437e-04 - mean_absolute_error: 0.0086 15/126 [==>...........................] - ETA: 0s - loss: 1.9155e-04 - mean_absolute_error: 0.0103 30/126 [======>.......................] - ETA: 0s - loss: 2.6257e-04 - mean_absolute_error: 0.0114 43/126 [=========>....................] - ETA: 0s - loss: 2.5239e-04 - mean_absolute_error: 0.0114 56/126 [============>.................] - ETA: 0s - loss: 2.5862e-04 - mean_absolute_error: 0.0115 70/126 [===============>..............] - ETA: 0s - loss: 2.5198e-04 - mean_absolute_error: 0.0115 87/126 [===================>..........] - ETA: 0s - loss: 2.6604e-04 - mean_absolute_error: 0.0120105/126 [========================>.....] - ETA: 0s - loss: 2.8412e-04 - mean_absolute_error: 0.0124122/126 [============================>.] - ETA: 0s - loss: 2.8283e-04 - mean_absolute_error: 0.0125126/126 [==============================] - 0s 4ms/step - loss: 2.8342e-04 - mean_absolute_error: 0.0125 - val_loss: 2.2266e-04 - val_mean_absolute_error: 0.0121
Epoch 39/100
1/126 [..............................] - ETA: 0s - loss: 1.6699e-04 - mean_absolute_error: 0.0105 20/126 [===>..........................] - ETA: 0s - loss: 2.4318e-04 - mean_absolute_error: 0.0115 39/126 [========>.....................] - ETA: 0s - loss: 2.6825e-04 - mean_absolute_error: 0.0121 57/126 [============>.................] - ETA: 0s - loss: 2.7988e-04 - mean_absolute_error: 0.0123 71/126 [===============>..............] - ETA: 0s - loss: 2.7313e-04 - mean_absolute_error: 0.0123 84/126 [===================>..........] - ETA: 0s - loss: 2.6255e-04 - mean_absolute_error: 0.0121 98/126 [======================>.......] - ETA: 0s - loss: 2.8476e-04 - mean_absolute_error: 0.0123113/126 [=========================>....] - ETA: 0s - loss: 2.9975e-04 - mean_absolute_error: 0.0127126/126 [==============================] - 0s 4ms/step - loss: 3.0523e-04 - mean_absolute_error: 0.0129 - val_loss: 1.5744e-04 - val_mean_absolute_error: 0.0102
Epoch 40/100
1/126 [..............................] - ETA: 0s - loss: 4.2373e-04 - mean_absolute_error: 0.0154 17/126 [===>..........................] - ETA: 0s - loss: 3.5179e-04 - mean_absolute_error: 0.0144 33/126 [======>.......................] - ETA: 0s - loss: 3.0589e-04 - mean_absolute_error: 0.0135 50/126 [==========>...................] - ETA: 0s - loss: 3.1530e-04 - mean_absolute_error: 0.0133 66/126 [==============>...............] - ETA: 0s - loss: 2.9106e-04 - mean_absolute_error: 0.0128 82/126 [==================>...........] - ETA: 0s - loss: 2.7539e-04 - mean_absolute_error: 0.0124 96/126 [=====================>........] - ETA: 0s - loss: 2.6497e-04 - mean_absolute_error: 0.0121112/126 [=========================>....] - ETA: 0s - loss: 2.7473e-04 - mean_absolute_error: 0.0124126/126 [==============================] - 0s 4ms/step - loss: 2.7674e-04 - mean_absolute_error: 0.0123 - val_loss: 1.2092e-04 - val_mean_absolute_error: 0.0088
Epoch 41/100
1/126 [..............................] - ETA: 0s - loss: 1.2940e-04 - mean_absolute_error: 0.0089 18/126 [===>..........................] - ETA: 0s - loss: 2.1777e-04 - mean_absolute_error: 0.0101 35/126 [=======>......................] - ETA: 0s - loss: 2.1683e-04 - mean_absolute_error: 0.0102 52/126 [===========>..................] - ETA: 0s - loss: 2.1216e-04 - mean_absolute_error: 0.0103 69/126 [===============>..............] - ETA: 0s - loss: 2.1018e-04 - mean_absolute_error: 0.0105 87/126 [===================>..........] - ETA: 0s - loss: 2.2999e-04 - mean_absolute_error: 0.0110105/126 [========================>.....] - ETA: 0s - loss: 2.4282e-04 - mean_absolute_error: 0.0113123/126 [============================>.] - ETA: 0s - loss: 2.5428e-04 - mean_absolute_error: 0.0116126/126 [==============================] - 0s 3ms/step - loss: 2.5870e-04 - mean_absolute_error: 0.0116 - val_loss: 1.6077e-04 - val_mean_absolute_error: 0.0100
Epoch 42/100
1/126 [..............................] - ETA: 0s - loss: 1.6538e-04 - mean_absolute_error: 0.0093 18/126 [===>..........................] - ETA: 0s - loss: 2.7452e-04 - mean_absolute_error: 0.0126 36/126 [=======>......................] - ETA: 0s - loss: 2.7587e-04 - mean_absolute_error: 0.0122 54/126 [===========>..................] - ETA: 0s - loss: 2.7137e-04 - mean_absolute_error: 0.0121 71/126 [===============>..............] - ETA: 0s - loss: 2.6080e-04 - mean_absolute_error: 0.0118 87/126 [===================>..........] - ETA: 0s - loss: 2.5188e-04 - mean_absolute_error: 0.0116104/126 [=======================>......] - ETA: 0s - loss: 2.5121e-04 - mean_absolute_error: 0.0115121/126 [===========================>..] - ETA: 0s - loss: 2.5243e-04 - mean_absolute_error: 0.0114126/126 [==============================] - 0s 3ms/step - loss: 2.4930e-04 - mean_absolute_error: 0.0114 - val_loss: 3.4108e-04 - val_mean_absolute_error: 0.0158
Epoch 43/100
1/126 [..............................] - ETA: 0s - loss: 4.1653e-04 - mean_absolute_error: 0.0160 19/126 [===>..........................] - ETA: 0s - loss: 2.6584e-04 - mean_absolute_error: 0.0124 37/126 [=======>......................] - ETA: 0s - loss: 2.8131e-04 - mean_absolute_error: 0.0127 54/126 [===========>..................] - ETA: 0s - loss: 2.7457e-04 - mean_absolute_error: 0.0125 70/126 [===============>..............] - ETA: 0s - loss: 2.7301e-04 - mean_absolute_error: 0.0123 86/126 [===================>..........] - ETA: 0s - loss: 2.7259e-04 - mean_absolute_error: 0.0122101/126 [=======================>......] - ETA: 0s - loss: 3.0399e-04 - mean_absolute_error: 0.0129117/126 [==========================>...] - ETA: 0s - loss: 3.0381e-04 - mean_absolute_error: 0.0130126/126 [==============================] - 0s 3ms/step - loss: 3.0092e-04 - mean_absolute_error: 0.0129 - val_loss: 1.1732e-04 - val_mean_absolute_error: 0.0086
Epoch 44/100
1/126 [..............................] - ETA: 0s - loss: 2.1535e-04 - mean_absolute_error: 0.0101 18/126 [===>..........................] - ETA: 0s - loss: 2.4903e-04 - mean_absolute_error: 0.0113 37/126 [=======>......................] - ETA: 0s - loss: 2.2659e-04 - mean_absolute_error: 0.0110 56/126 [============>.................] - ETA: 0s - loss: 2.3821e-04 - mean_absolute_error: 0.0115 75/126 [================>.............] - ETA: 0s - loss: 2.4586e-04 - mean_absolute_error: 0.0117 95/126 [=====================>........] - ETA: 0s - loss: 2.5634e-04 - mean_absolute_error: 0.0118115/126 [==========================>...] - ETA: 0s - loss: 2.5585e-04 - mean_absolute_error: 0.0117126/126 [==============================] - 0s 3ms/step - loss: 2.5121e-04 - mean_absolute_error: 0.0116 - val_loss: 1.6603e-04 - val_mean_absolute_error: 0.0102
Epoch 45/100
1/126 [..............................] - ETA: 0s - loss: 6.4985e-04 - mean_absolute_error: 0.0169 22/126 [====>.........................] - ETA: 0s - loss: 2.7849e-04 - mean_absolute_error: 0.0119 42/126 [=========>....................] - ETA: 0s - loss: 2.7111e-04 - mean_absolute_error: 0.0121 62/126 [=============>................] - ETA: 0s - loss: 2.7753e-04 - mean_absolute_error: 0.0125 81/126 [==================>...........] - ETA: 0s - loss: 2.8840e-04 - mean_absolute_error: 0.0127101/126 [=======================>......] - ETA: 0s - loss: 2.9124e-04 - mean_absolute_error: 0.0125121/126 [===========================>..] - ETA: 0s - loss: 2.7616e-04 - mean_absolute_error: 0.0122126/126 [==============================] - 0s 3ms/step - loss: 2.7313e-04 - mean_absolute_error: 0.0121 - val_loss: 2.5681e-04 - val_mean_absolute_error: 0.0135
Epoch 46/100
1/126 [..............................] - ETA: 0s - loss: 2.9135e-04 - mean_absolute_error: 0.0143 21/126 [====>.........................] - ETA: 0s - loss: 2.3222e-04 - mean_absolute_error: 0.0119 41/126 [========>.....................] - ETA: 0s - loss: 2.5038e-04 - mean_absolute_error: 0.0122 61/126 [=============>................] - ETA: 0s - loss: 2.8078e-04 - mean_absolute_error: 0.0129 81/126 [==================>...........] - ETA: 0s - loss: 2.8056e-04 - mean_absolute_error: 0.0127100/126 [======================>.......] - ETA: 0s - loss: 2.8061e-04 - mean_absolute_error: 0.0126120/126 [===========================>..] - ETA: 0s - loss: 2.8083e-04 - mean_absolute_error: 0.0125126/126 [==============================] - 0s 3ms/step - loss: 2.8511e-04 - mean_absolute_error: 0.0125 - val_loss: 1.3471e-04 - val_mean_absolute_error: 0.0091
Epoch 47/100
1/126 [..............................] - ETA: 0s - loss: 1.2976e-04 - mean_absolute_error: 0.0085 22/126 [====>.........................] - ETA: 0s - loss: 2.4620e-04 - mean_absolute_error: 0.0109 41/126 [========>.....................] - ETA: 0s - loss: 2.6055e-04 - mean_absolute_error: 0.0112 61/126 [=============>................] - ETA: 0s - loss: 2.7217e-04 - mean_absolute_error: 0.0119 80/126 [==================>...........] - ETA: 0s - loss: 2.7064e-04 - mean_absolute_error: 0.0118100/126 [======================>.......] - ETA: 0s - loss: 2.5698e-04 - mean_absolute_error: 0.0116121/126 [===========================>..] - ETA: 0s - loss: 2.5371e-04 - mean_absolute_error: 0.0116126/126 [==============================] - 0s 3ms/step - loss: 2.5361e-04 - mean_absolute_error: 0.0116 - val_loss: 1.4400e-04 - val_mean_absolute_error: 0.0094
Epoch 48/100
1/126 [..............................] - ETA: 0s - loss: 2.3046e-04 - mean_absolute_error: 0.0131 21/126 [====>.........................] - ETA: 0s - loss: 2.1639e-04 - mean_absolute_error: 0.0109 42/126 [=========>....................] - ETA: 0s - loss: 2.2725e-04 - mean_absolute_error: 0.0112 62/126 [=============>................] - ETA: 0s - loss: 2.4740e-04 - mean_absolute_error: 0.0116 82/126 [==================>...........] - ETA: 0s - loss: 2.5509e-04 - mean_absolute_error: 0.0119101/126 [=======================>......] - ETA: 0s - loss: 2.6348e-04 - mean_absolute_error: 0.0120120/126 [===========================>..] - ETA: 0s - loss: 2.6289e-04 - mean_absolute_error: 0.0119126/126 [==============================] - 0s 3ms/step - loss: 2.6165e-04 - mean_absolute_error: 0.0118 - val_loss: 1.3823e-04 - val_mean_absolute_error: 0.0092
Epoch 49/100
1/126 [..............................] - ETA: 0s - loss: 5.4884e-04 - mean_absolute_error: 0.0123 21/126 [====>.........................] - ETA: 0s - loss: 2.6894e-04 - mean_absolute_error: 0.0122 41/126 [========>.....................] - ETA: 0s - loss: 2.7632e-04 - mean_absolute_error: 0.0120 61/126 [=============>................] - ETA: 0s - loss: 2.5826e-04 - mean_absolute_error: 0.0116 81/126 [==================>...........] - ETA: 0s - loss: 2.4835e-04 - mean_absolute_error: 0.0115102/126 [=======================>......] - ETA: 0s - loss: 2.4850e-04 - mean_absolute_error: 0.0114122/126 [============================>.] - ETA: 0s - loss: 2.4332e-04 - mean_absolute_error: 0.0113126/126 [==============================] - 0s 3ms/step - loss: 2.4573e-04 - mean_absolute_error: 0.0114 - val_loss: 1.1153e-04 - val_mean_absolute_error: 0.0082
Epoch 50/100
1/126 [..............................] - ETA: 0s - loss: 1.5577e-04 - mean_absolute_error: 0.0099 22/126 [====>.........................] - ETA: 0s - loss: 2.6798e-04 - mean_absolute_error: 0.0124 42/126 [=========>....................] - ETA: 0s - loss: 2.5673e-04 - mean_absolute_error: 0.0119 62/126 [=============>................] - ETA: 0s - loss: 2.4175e-04 - mean_absolute_error: 0.0114 82/126 [==================>...........] - ETA: 0s - loss: 2.4602e-04 - mean_absolute_error: 0.0114102/126 [=======================>......] - ETA: 0s - loss: 2.4116e-04 - mean_absolute_error: 0.0114123/126 [============================>.] - ETA: 0s - loss: 2.5685e-04 - mean_absolute_error: 0.0117126/126 [==============================] - 0s 3ms/step - loss: 2.6097e-04 - mean_absolute_error: 0.0118 - val_loss: 3.1105e-04 - val_mean_absolute_error: 0.0152
Epoch 51/100
1/126 [..............................] - ETA: 0s - loss: 4.9625e-04 - mean_absolute_error: 0.0174 21/126 [====>.........................] - ETA: 0s - loss: 3.3126e-04 - mean_absolute_error: 0.0136 42/126 [=========>....................] - ETA: 0s - loss: 2.8333e-04 - mean_absolute_error: 0.0122 62/126 [=============>................] - ETA: 0s - loss: 2.6853e-04 - mean_absolute_error: 0.0118 82/126 [==================>...........] - ETA: 0s - loss: 2.5717e-04 - mean_absolute_error: 0.0116102/126 [=======================>......] - ETA: 0s - loss: 2.6440e-04 - mean_absolute_error: 0.0118122/126 [============================>.] - ETA: 0s - loss: 2.5920e-04 - mean_absolute_error: 0.0118126/126 [==============================] - 0s 3ms/step - loss: 2.5780e-04 - mean_absolute_error: 0.0117 - val_loss: 1.6268e-04 - val_mean_absolute_error: 0.0104
Epoch 52/100
1/126 [..............................] - ETA: 0s - loss: 1.9324e-04 - mean_absolute_error: 0.0116 21/126 [====>.........................] - ETA: 0s - loss: 2.8477e-04 - mean_absolute_error: 0.0127 42/126 [=========>....................] - ETA: 0s - loss: 3.1036e-04 - mean_absolute_error: 0.0132 62/126 [=============>................] - ETA: 0s - loss: 2.9698e-04 - mean_absolute_error: 0.0129 82/126 [==================>...........] - ETA: 0s - loss: 2.8238e-04 - mean_absolute_error: 0.0124103/126 [=======================>......] - ETA: 0s - loss: 2.8227e-04 - mean_absolute_error: 0.0124123/126 [============================>.] - ETA: 0s - loss: 2.7940e-04 - mean_absolute_error: 0.0123126/126 [==============================] - 0s 3ms/step - loss: 2.7808e-04 - mean_absolute_error: 0.0123 - val_loss: 2.0296e-04 - val_mean_absolute_error: 0.0118
Epoch 53/100
1/126 [..............................] - ETA: 0s - loss: 1.5145e-04 - mean_absolute_error: 0.0102 22/126 [====>.........................] - ETA: 0s - loss: 2.6668e-04 - mean_absolute_error: 0.0117 42/126 [=========>....................] - ETA: 0s - loss: 2.5801e-04 - mean_absolute_error: 0.0114 62/126 [=============>................] - ETA: 0s - loss: 2.5752e-04 - mean_absolute_error: 0.0115 82/126 [==================>...........] - ETA: 0s - loss: 2.5331e-04 - mean_absolute_error: 0.0114102/126 [=======================>......] - ETA: 0s - loss: 2.4315e-04 - mean_absolute_error: 0.0113123/126 [============================>.] - ETA: 0s - loss: 2.4034e-04 - mean_absolute_error: 0.0112126/126 [==============================] - 0s 3ms/step - loss: 2.3823e-04 - mean_absolute_error: 0.0112 - val_loss: 1.3501e-04 - val_mean_absolute_error: 0.0091
Epoch 54/100
1/126 [..............................] - ETA: 0s - loss: 2.6000e-04 - mean_absolute_error: 0.0129 21/126 [====>.........................] - ETA: 0s - loss: 1.9627e-04 - mean_absolute_error: 0.0104 41/126 [========>.....................] - ETA: 0s - loss: 2.5055e-04 - mean_absolute_error: 0.0116 60/126 [=============>................] - ETA: 0s - loss: 2.3964e-04 - mean_absolute_error: 0.0114 80/126 [==================>...........] - ETA: 0s - loss: 2.4896e-04 - mean_absolute_error: 0.0115 99/126 [======================>.......] - ETA: 0s - loss: 2.5459e-04 - mean_absolute_error: 0.0116119/126 [===========================>..] - ETA: 0s - loss: 2.4923e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.4805e-04 - mean_absolute_error: 0.0114 - val_loss: 1.1575e-04 - val_mean_absolute_error: 0.0083
Epoch 55/100
1/126 [..............................] - ETA: 0s - loss: 2.3349e-04 - mean_absolute_error: 0.0101 21/126 [====>.........................] - ETA: 0s - loss: 2.5794e-04 - mean_absolute_error: 0.0117 41/126 [========>.....................] - ETA: 0s - loss: 2.5406e-04 - mean_absolute_error: 0.0120 61/126 [=============>................] - ETA: 0s - loss: 2.5156e-04 - mean_absolute_error: 0.0119 81/126 [==================>...........] - ETA: 0s - loss: 2.5408e-04 - mean_absolute_error: 0.0118101/126 [=======================>......] - ETA: 0s - loss: 2.5607e-04 - mean_absolute_error: 0.0119121/126 [===========================>..] - ETA: 0s - loss: 2.5429e-04 - mean_absolute_error: 0.0118126/126 [==============================] - 0s 3ms/step - loss: 2.5380e-04 - mean_absolute_error: 0.0117 - val_loss: 1.7461e-04 - val_mean_absolute_error: 0.0105
Epoch 56/100
1/126 [..............................] - ETA: 0s - loss: 1.4654e-04 - mean_absolute_error: 0.0098 21/126 [====>.........................] - ETA: 0s - loss: 2.6480e-04 - mean_absolute_error: 0.0118 42/126 [=========>....................] - ETA: 0s - loss: 2.5616e-04 - mean_absolute_error: 0.0114 61/126 [=============>................] - ETA: 0s - loss: 2.7423e-04 - mean_absolute_error: 0.0120 81/126 [==================>...........] - ETA: 0s - loss: 2.6495e-04 - mean_absolute_error: 0.0119101/126 [=======================>......] - ETA: 0s - loss: 2.8557e-04 - mean_absolute_error: 0.0125121/126 [===========================>..] - ETA: 0s - loss: 3.0110e-04 - mean_absolute_error: 0.0128126/126 [==============================] - 0s 3ms/step - loss: 2.9802e-04 - mean_absolute_error: 0.0127 - val_loss: 1.1390e-04 - val_mean_absolute_error: 0.0083
Epoch 57/100
1/126 [..............................] - ETA: 0s - loss: 1.2085e-04 - mean_absolute_error: 0.0094 21/126 [====>.........................] - ETA: 0s - loss: 2.2551e-04 - mean_absolute_error: 0.0108 42/126 [=========>....................] - ETA: 0s - loss: 2.5285e-04 - mean_absolute_error: 0.0119 62/126 [=============>................] - ETA: 0s - loss: 2.3289e-04 - mean_absolute_error: 0.0113 82/126 [==================>...........] - ETA: 0s - loss: 2.3637e-04 - mean_absolute_error: 0.0112102/126 [=======================>......] - ETA: 0s - loss: 2.4464e-04 - mean_absolute_error: 0.0112121/126 [===========================>..] - ETA: 0s - loss: 2.4430e-04 - mean_absolute_error: 0.0112126/126 [==============================] - 0s 3ms/step - loss: 2.4273e-04 - mean_absolute_error: 0.0112 - val_loss: 1.0865e-04 - val_mean_absolute_error: 0.0081
Epoch 58/100
1/126 [..............................] - ETA: 0s - loss: 1.2006e-04 - mean_absolute_error: 0.0086 22/126 [====>.........................] - ETA: 0s - loss: 3.3162e-04 - mean_absolute_error: 0.0134 42/126 [=========>....................] - ETA: 0s - loss: 2.8932e-04 - mean_absolute_error: 0.0126 62/126 [=============>................] - ETA: 0s - loss: 2.9845e-04 - mean_absolute_error: 0.0127 81/126 [==================>...........] - ETA: 0s - loss: 2.7893e-04 - mean_absolute_error: 0.0121101/126 [=======================>......] - ETA: 0s - loss: 2.6943e-04 - mean_absolute_error: 0.0119121/126 [===========================>..] - ETA: 0s - loss: 2.6145e-04 - mean_absolute_error: 0.0118126/126 [==============================] - 0s 3ms/step - loss: 2.6184e-04 - mean_absolute_error: 0.0119 - val_loss: 1.5318e-04 - val_mean_absolute_error: 0.0101
Epoch 59/100
1/126 [..............................] - ETA: 0s - loss: 1.5303e-04 - mean_absolute_error: 0.0101 22/126 [====>.........................] - ETA: 0s - loss: 2.1867e-04 - mean_absolute_error: 0.0108 42/126 [=========>....................] - ETA: 0s - loss: 2.4359e-04 - mean_absolute_error: 0.0113 63/126 [==============>...............] - ETA: 0s - loss: 2.3964e-04 - mean_absolute_error: 0.0112 83/126 [==================>...........] - ETA: 0s - loss: 2.3318e-04 - mean_absolute_error: 0.0111103/126 [=======================>......] - ETA: 0s - loss: 2.5026e-04 - mean_absolute_error: 0.0115122/126 [============================>.] - ETA: 0s - loss: 2.4507e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.4400e-04 - mean_absolute_error: 0.0114 - val_loss: 1.5162e-04 - val_mean_absolute_error: 0.0097
Epoch 60/100
1/126 [..............................] - ETA: 0s - loss: 1.2695e-04 - mean_absolute_error: 0.0096 21/126 [====>.........................] - ETA: 0s - loss: 2.0499e-04 - mean_absolute_error: 0.0104 41/126 [========>.....................] - ETA: 0s - loss: 2.1812e-04 - mean_absolute_error: 0.0106 61/126 [=============>................] - ETA: 0s - loss: 2.3616e-04 - mean_absolute_error: 0.0111 81/126 [==================>...........] - ETA: 0s - loss: 3.2781e-04 - mean_absolute_error: 0.0132102/126 [=======================>......] - ETA: 0s - loss: 3.1441e-04 - mean_absolute_error: 0.0130123/126 [============================>.] - ETA: 0s - loss: 3.0849e-04 - mean_absolute_error: 0.0129126/126 [==============================] - 0s 3ms/step - loss: 3.0798e-04 - mean_absolute_error: 0.0129 - val_loss: 1.0716e-04 - val_mean_absolute_error: 0.0081
Epoch 61/100
1/126 [..............................] - ETA: 0s - loss: 1.3674e-04 - mean_absolute_error: 0.0100 21/126 [====>.........................] - ETA: 0s - loss: 3.3268e-04 - mean_absolute_error: 0.0133 42/126 [=========>....................] - ETA: 0s - loss: 2.8362e-04 - mean_absolute_error: 0.0124 62/126 [=============>................] - ETA: 0s - loss: 2.7993e-04 - mean_absolute_error: 0.0121 82/126 [==================>...........] - ETA: 0s - loss: 2.7280e-04 - mean_absolute_error: 0.0120101/126 [=======================>......] - ETA: 0s - loss: 2.6311e-04 - mean_absolute_error: 0.0119120/126 [===========================>..] - ETA: 0s - loss: 2.6259e-04 - mean_absolute_error: 0.0118126/126 [==============================] - 0s 3ms/step - loss: 2.6419e-04 - mean_absolute_error: 0.0119 - val_loss: 1.7026e-04 - val_mean_absolute_error: 0.0104
Epoch 62/100
1/126 [..............................] - ETA: 0s - loss: 2.2298e-04 - mean_absolute_error: 0.0115 22/126 [====>.........................] - ETA: 0s - loss: 2.9922e-04 - mean_absolute_error: 0.0126 42/126 [=========>....................] - ETA: 0s - loss: 2.9492e-04 - mean_absolute_error: 0.0122 63/126 [==============>...............] - ETA: 0s - loss: 2.6657e-04 - mean_absolute_error: 0.0118 83/126 [==================>...........] - ETA: 0s - loss: 2.4740e-04 - mean_absolute_error: 0.0114103/126 [=======================>......] - ETA: 0s - loss: 2.3837e-04 - mean_absolute_error: 0.0112122/126 [============================>.] - ETA: 0s - loss: 2.3167e-04 - mean_absolute_error: 0.0111126/126 [==============================] - 0s 3ms/step - loss: 2.3561e-04 - mean_absolute_error: 0.0111 - val_loss: 1.4452e-04 - val_mean_absolute_error: 0.0094
Epoch 63/100
1/126 [..............................] - ETA: 0s - loss: 9.5535e-05 - mean_absolute_error: 0.0079 21/126 [====>.........................] - ETA: 0s - loss: 2.6520e-04 - mean_absolute_error: 0.0119 42/126 [=========>....................] - ETA: 0s - loss: 2.3924e-04 - mean_absolute_error: 0.0113 62/126 [=============>................] - ETA: 0s - loss: 2.2802e-04 - mean_absolute_error: 0.0112 82/126 [==================>...........] - ETA: 0s - loss: 2.2739e-04 - mean_absolute_error: 0.0112102/126 [=======================>......] - ETA: 0s - loss: 2.3336e-04 - mean_absolute_error: 0.0111123/126 [============================>.] - ETA: 0s - loss: 2.3505e-04 - mean_absolute_error: 0.0111126/126 [==============================] - 0s 3ms/step - loss: 2.3323e-04 - mean_absolute_error: 0.0110 - val_loss: 1.6821e-04 - val_mean_absolute_error: 0.0103
Epoch 64/100
1/126 [..............................] - ETA: 0s - loss: 1.8017e-04 - mean_absolute_error: 0.0109 21/126 [====>.........................] - ETA: 0s - loss: 2.1136e-04 - mean_absolute_error: 0.0107 41/126 [========>.....................] - ETA: 0s - loss: 2.2573e-04 - mean_absolute_error: 0.0110 61/126 [=============>................] - ETA: 0s - loss: 2.1171e-04 - mean_absolute_error: 0.0108 81/126 [==================>...........] - ETA: 0s - loss: 2.2881e-04 - mean_absolute_error: 0.0110101/126 [=======================>......] - ETA: 0s - loss: 2.2238e-04 - mean_absolute_error: 0.0109121/126 [===========================>..] - ETA: 0s - loss: 2.3404e-04 - mean_absolute_error: 0.0111126/126 [==============================] - 0s 3ms/step - loss: 2.3125e-04 - mean_absolute_error: 0.0111 - val_loss: 1.2848e-04 - val_mean_absolute_error: 0.0091
Epoch 65/100
1/126 [..............................] - ETA: 0s - loss: 1.1091e-04 - mean_absolute_error: 0.0088 21/126 [====>.........................] - ETA: 0s - loss: 2.6177e-04 - mean_absolute_error: 0.0111 41/126 [========>.....................] - ETA: 0s - loss: 2.4832e-04 - mean_absolute_error: 0.0112 61/126 [=============>................] - ETA: 0s - loss: 2.3154e-04 - mean_absolute_error: 0.0111 79/126 [=================>............] - ETA: 0s - loss: 2.2696e-04 - mean_absolute_error: 0.0109 99/126 [======================>.......] - ETA: 0s - loss: 2.3244e-04 - mean_absolute_error: 0.0110119/126 [===========================>..] - ETA: 0s - loss: 2.3297e-04 - mean_absolute_error: 0.0110126/126 [==============================] - 0s 3ms/step - loss: 2.3120e-04 - mean_absolute_error: 0.0110 - val_loss: 1.2033e-04 - val_mean_absolute_error: 0.0085
Epoch 66/100
1/126 [..............................] - ETA: 0s - loss: 4.8714e-04 - mean_absolute_error: 0.0139 21/126 [====>.........................] - ETA: 0s - loss: 2.3216e-04 - mean_absolute_error: 0.0117 42/126 [=========>....................] - ETA: 0s - loss: 2.6303e-04 - mean_absolute_error: 0.0121 62/126 [=============>................] - ETA: 0s - loss: 2.7456e-04 - mean_absolute_error: 0.0123 81/126 [==================>...........] - ETA: 0s - loss: 2.5952e-04 - mean_absolute_error: 0.0120101/126 [=======================>......] - ETA: 0s - loss: 2.3980e-04 - mean_absolute_error: 0.0115121/126 [===========================>..] - ETA: 0s - loss: 2.4908e-04 - mean_absolute_error: 0.0116126/126 [==============================] - 0s 3ms/step - loss: 2.4957e-04 - mean_absolute_error: 0.0116 - val_loss: 1.4881e-04 - val_mean_absolute_error: 0.0099
Epoch 67/100
1/126 [..............................] - ETA: 0s - loss: 9.3106e-05 - mean_absolute_error: 0.0076 21/126 [====>.........................] - ETA: 0s - loss: 2.1647e-04 - mean_absolute_error: 0.0102 41/126 [========>.....................] - ETA: 0s - loss: 2.2492e-04 - mean_absolute_error: 0.0105 61/126 [=============>................] - ETA: 0s - loss: 2.2352e-04 - mean_absolute_error: 0.0108 81/126 [==================>...........] - ETA: 0s - loss: 2.2526e-04 - mean_absolute_error: 0.0110101/126 [=======================>......] - ETA: 0s - loss: 2.5839e-04 - mean_absolute_error: 0.0119122/126 [============================>.] - ETA: 0s - loss: 2.4841e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.4749e-04 - mean_absolute_error: 0.0115 - val_loss: 1.0468e-04 - val_mean_absolute_error: 0.0080
Epoch 68/100
1/126 [..............................] - ETA: 0s - loss: 1.7305e-04 - mean_absolute_error: 0.0103 22/126 [====>.........................] - ETA: 0s - loss: 2.1011e-04 - mean_absolute_error: 0.0105 42/126 [=========>....................] - ETA: 0s - loss: 2.5157e-04 - mean_absolute_error: 0.0116 61/126 [=============>................] - ETA: 0s - loss: 2.6185e-04 - mean_absolute_error: 0.0119 81/126 [==================>...........] - ETA: 0s - loss: 2.5703e-04 - mean_absolute_error: 0.0117101/126 [=======================>......] - ETA: 0s - loss: 2.5045e-04 - mean_absolute_error: 0.0116121/126 [===========================>..] - ETA: 0s - loss: 2.4030e-04 - mean_absolute_error: 0.0114126/126 [==============================] - 0s 3ms/step - loss: 2.4057e-04 - mean_absolute_error: 0.0113 - val_loss: 2.2185e-04 - val_mean_absolute_error: 0.0122
Epoch 69/100
1/126 [..............................] - ETA: 0s - loss: 4.2155e-04 - mean_absolute_error: 0.0153 21/126 [====>.........................] - ETA: 0s - loss: 2.2510e-04 - mean_absolute_error: 0.0106 41/126 [========>.....................] - ETA: 0s - loss: 2.2933e-04 - mean_absolute_error: 0.0108 59/126 [=============>................] - ETA: 0s - loss: 2.2420e-04 - mean_absolute_error: 0.0109 76/126 [=================>............] - ETA: 0s - loss: 2.2367e-04 - mean_absolute_error: 0.0109 96/126 [=====================>........] - ETA: 0s - loss: 2.1684e-04 - mean_absolute_error: 0.0107116/126 [==========================>...] - ETA: 0s - loss: 2.3448e-04 - mean_absolute_error: 0.0111126/126 [==============================] - 0s 3ms/step - loss: 2.3388e-04 - mean_absolute_error: 0.0111 - val_loss: 1.0768e-04 - val_mean_absolute_error: 0.0080
Epoch 70/100
1/126 [..............................] - ETA: 0s - loss: 5.5516e-04 - mean_absolute_error: 0.0100 21/126 [====>.........................] - ETA: 0s - loss: 2.1012e-04 - mean_absolute_error: 0.0103 42/126 [=========>....................] - ETA: 0s - loss: 2.0566e-04 - mean_absolute_error: 0.0104 62/126 [=============>................] - ETA: 0s - loss: 2.4163e-04 - mean_absolute_error: 0.0113 81/126 [==================>...........] - ETA: 0s - loss: 2.7493e-04 - mean_absolute_error: 0.0122101/126 [=======================>......] - ETA: 0s - loss: 2.9072e-04 - mean_absolute_error: 0.0127121/126 [===========================>..] - ETA: 0s - loss: 2.8331e-04 - mean_absolute_error: 0.0125126/126 [==============================] - 0s 3ms/step - loss: 2.7861e-04 - mean_absolute_error: 0.0124 - val_loss: 1.0554e-04 - val_mean_absolute_error: 0.0080
Epoch 71/100
1/126 [..............................] - ETA: 0s - loss: 2.7237e-04 - mean_absolute_error: 0.0104 21/126 [====>.........................] - ETA: 0s - loss: 1.9115e-04 - mean_absolute_error: 0.0103 41/126 [========>.....................] - ETA: 0s - loss: 1.9520e-04 - mean_absolute_error: 0.0106 61/126 [=============>................] - ETA: 0s - loss: 1.9445e-04 - mean_absolute_error: 0.0105 80/126 [==================>...........] - ETA: 0s - loss: 2.1989e-04 - mean_absolute_error: 0.0109100/126 [======================>.......] - ETA: 0s - loss: 2.1716e-04 - mean_absolute_error: 0.0107120/126 [===========================>..] - ETA: 0s - loss: 2.2979e-04 - mean_absolute_error: 0.0110126/126 [==============================] - 0s 3ms/step - loss: 2.3007e-04 - mean_absolute_error: 0.0110 - val_loss: 1.0716e-04 - val_mean_absolute_error: 0.0082
Epoch 72/100
1/126 [..............................] - ETA: 0s - loss: 3.2914e-04 - mean_absolute_error: 0.0117 21/126 [====>.........................] - ETA: 0s - loss: 2.4934e-04 - mean_absolute_error: 0.0107 41/126 [========>.....................] - ETA: 0s - loss: 2.6242e-04 - mean_absolute_error: 0.0117 62/126 [=============>................] - ETA: 0s - loss: 2.4290e-04 - mean_absolute_error: 0.0112 81/126 [==================>...........] - ETA: 0s - loss: 2.3378e-04 - mean_absolute_error: 0.0112101/126 [=======================>......] - ETA: 0s - loss: 2.3259e-04 - mean_absolute_error: 0.0111121/126 [===========================>..] - ETA: 0s - loss: 2.3089e-04 - mean_absolute_error: 0.0111126/126 [==============================] - 0s 3ms/step - loss: 2.3283e-04 - mean_absolute_error: 0.0111 - val_loss: 1.6918e-04 - val_mean_absolute_error: 0.0107
Epoch 73/100
1/126 [..............................] - ETA: 0s - loss: 5.7740e-04 - mean_absolute_error: 0.0172 21/126 [====>.........................] - ETA: 0s - loss: 2.9054e-04 - mean_absolute_error: 0.0120 41/126 [========>.....................] - ETA: 0s - loss: 2.4965e-04 - mean_absolute_error: 0.0111 61/126 [=============>................] - ETA: 0s - loss: 2.2926e-04 - mean_absolute_error: 0.0109 81/126 [==================>...........] - ETA: 0s - loss: 2.2055e-04 - mean_absolute_error: 0.0107101/126 [=======================>......] - ETA: 0s - loss: 2.1846e-04 - mean_absolute_error: 0.0107121/126 [===========================>..] - ETA: 0s - loss: 2.1931e-04 - mean_absolute_error: 0.0107126/126 [==============================] - 0s 3ms/step - loss: 2.1805e-04 - mean_absolute_error: 0.0107 - val_loss: 1.0464e-04 - val_mean_absolute_error: 0.0079
Epoch 74/100
1/126 [..............................] - ETA: 0s - loss: 3.0835e-04 - mean_absolute_error: 0.0116 21/126 [====>.........................] - ETA: 0s - loss: 2.4331e-04 - mean_absolute_error: 0.0116 41/126 [========>.....................] - ETA: 0s - loss: 2.2899e-04 - mean_absolute_error: 0.0112 61/126 [=============>................] - ETA: 0s - loss: 2.3141e-04 - mean_absolute_error: 0.0113 81/126 [==================>...........] - ETA: 0s - loss: 2.3976e-04 - mean_absolute_error: 0.0114101/126 [=======================>......] - ETA: 0s - loss: 2.3961e-04 - mean_absolute_error: 0.0115121/126 [===========================>..] - ETA: 0s - loss: 2.5061e-04 - mean_absolute_error: 0.0118126/126 [==============================] - 0s 3ms/step - loss: 2.5051e-04 - mean_absolute_error: 0.0118 - val_loss: 1.3710e-04 - val_mean_absolute_error: 0.0095
Epoch 75/100
1/126 [..............................] - ETA: 0s - loss: 2.0395e-04 - mean_absolute_error: 0.0107 22/126 [====>.........................] - ETA: 0s - loss: 2.2265e-04 - mean_absolute_error: 0.0106 42/126 [=========>....................] - ETA: 0s - loss: 2.5909e-04 - mean_absolute_error: 0.0113 62/126 [=============>................] - ETA: 0s - loss: 2.4702e-04 - mean_absolute_error: 0.0112 82/126 [==================>...........] - ETA: 0s - loss: 2.4789e-04 - mean_absolute_error: 0.0113102/126 [=======================>......] - ETA: 0s - loss: 2.4621e-04 - mean_absolute_error: 0.0114121/126 [===========================>..] - ETA: 0s - loss: 2.4248e-04 - mean_absolute_error: 0.0114126/126 [==============================] - 0s 3ms/step - loss: 2.4238e-04 - mean_absolute_error: 0.0114 - val_loss: 1.7289e-04 - val_mean_absolute_error: 0.0108
Epoch 76/100
1/126 [..............................] - ETA: 0s - loss: 2.1519e-04 - mean_absolute_error: 0.0118 20/126 [===>..........................] - ETA: 0s - loss: 2.5173e-04 - mean_absolute_error: 0.0120 40/126 [========>.....................] - ETA: 0s - loss: 2.4268e-04 - mean_absolute_error: 0.0112 60/126 [=============>................] - ETA: 0s - loss: 2.2313e-04 - mean_absolute_error: 0.0108 80/126 [==================>...........] - ETA: 0s - loss: 2.2315e-04 - mean_absolute_error: 0.0108100/126 [======================>.......] - ETA: 0s - loss: 2.2853e-04 - mean_absolute_error: 0.0109120/126 [===========================>..] - ETA: 0s - loss: 2.2555e-04 - mean_absolute_error: 0.0109126/126 [==============================] - 0s 3ms/step - loss: 2.2153e-04 - mean_absolute_error: 0.0108 - val_loss: 9.9683e-05 - val_mean_absolute_error: 0.0078
Epoch 77/100
1/126 [..............................] - ETA: 0s - loss: 7.3775e-05 - mean_absolute_error: 0.0062 21/126 [====>.........................] - ETA: 0s - loss: 1.6017e-04 - mean_absolute_error: 0.0095 41/126 [========>.....................] - ETA: 0s - loss: 1.9629e-04 - mean_absolute_error: 0.0102 61/126 [=============>................] - ETA: 0s - loss: 2.1983e-04 - mean_absolute_error: 0.0110 80/126 [==================>...........] - ETA: 0s - loss: 2.4478e-04 - mean_absolute_error: 0.0117100/126 [======================>.......] - ETA: 0s - loss: 2.5443e-04 - mean_absolute_error: 0.0119120/126 [===========================>..] - ETA: 0s - loss: 2.6175e-04 - mean_absolute_error: 0.0120126/126 [==============================] - 0s 3ms/step - loss: 2.5869e-04 - mean_absolute_error: 0.0119 - val_loss: 1.0477e-04 - val_mean_absolute_error: 0.0081
Epoch 78/100
1/126 [..............................] - ETA: 0s - loss: 1.4365e-04 - mean_absolute_error: 0.0083 21/126 [====>.........................] - ETA: 0s - loss: 2.1663e-04 - mean_absolute_error: 0.0108 41/126 [========>.....................] - ETA: 0s - loss: 2.1970e-04 - mean_absolute_error: 0.0109 61/126 [=============>................] - ETA: 0s - loss: 2.2170e-04 - mean_absolute_error: 0.0109 81/126 [==================>...........] - ETA: 0s - loss: 2.3360e-04 - mean_absolute_error: 0.0112101/126 [=======================>......] - ETA: 0s - loss: 2.3273e-04 - mean_absolute_error: 0.0112120/126 [===========================>..] - ETA: 0s - loss: 2.5019e-04 - mean_absolute_error: 0.0116126/126 [==============================] - 0s 3ms/step - loss: 2.4817e-04 - mean_absolute_error: 0.0116 - val_loss: 1.2130e-04 - val_mean_absolute_error: 0.0086
Epoch 79/100
1/126 [..............................] - ETA: 0s - loss: 1.4869e-04 - mean_absolute_error: 0.0100 21/126 [====>.........................] - ETA: 0s - loss: 2.3562e-04 - mean_absolute_error: 0.0108 41/126 [========>.....................] - ETA: 0s - loss: 2.2687e-04 - mean_absolute_error: 0.0107 60/126 [=============>................] - ETA: 0s - loss: 2.3746e-04 - mean_absolute_error: 0.0108 79/126 [=================>............] - ETA: 0s - loss: 2.2273e-04 - mean_absolute_error: 0.0106 98/126 [======================>.......] - ETA: 0s - loss: 2.1845e-04 - mean_absolute_error: 0.0106118/126 [===========================>..] - ETA: 0s - loss: 2.1121e-04 - mean_absolute_error: 0.0105126/126 [==============================] - 0s 3ms/step - loss: 2.1143e-04 - mean_absolute_error: 0.0105 - val_loss: 1.2692e-04 - val_mean_absolute_error: 0.0088
Epoch 80/100
1/126 [..............................] - ETA: 0s - loss: 1.2746e-04 - mean_absolute_error: 0.0089 22/126 [====>.........................] - ETA: 0s - loss: 2.1857e-04 - mean_absolute_error: 0.0113 42/126 [=========>....................] - ETA: 0s - loss: 2.3262e-04 - mean_absolute_error: 0.0112 63/126 [==============>...............] - ETA: 0s - loss: 2.2969e-04 - mean_absolute_error: 0.0109 84/126 [===================>..........] - ETA: 0s - loss: 2.2090e-04 - mean_absolute_error: 0.0107104/126 [=======================>......] - ETA: 0s - loss: 2.2104e-04 - mean_absolute_error: 0.0107124/126 [============================>.] - ETA: 0s - loss: 2.1199e-04 - mean_absolute_error: 0.0105126/126 [==============================] - 0s 3ms/step - loss: 2.1085e-04 - mean_absolute_error: 0.0105 - val_loss: 1.1631e-04 - val_mean_absolute_error: 0.0084
Epoch 81/100
1/126 [..............................] - ETA: 0s - loss: 1.0201e-04 - mean_absolute_error: 0.0078 22/126 [====>.........................] - ETA: 0s - loss: 2.1974e-04 - mean_absolute_error: 0.0105 42/126 [=========>....................] - ETA: 0s - loss: 2.1261e-04 - mean_absolute_error: 0.0106 62/126 [=============>................] - ETA: 0s - loss: 2.2434e-04 - mean_absolute_error: 0.0107 81/126 [==================>...........] - ETA: 0s - loss: 2.3214e-04 - mean_absolute_error: 0.0111101/126 [=======================>......] - ETA: 0s - loss: 2.3527e-04 - mean_absolute_error: 0.0111120/126 [===========================>..] - ETA: 0s - loss: 2.3405e-04 - mean_absolute_error: 0.0112126/126 [==============================] - 0s 3ms/step - loss: 2.3326e-04 - mean_absolute_error: 0.0111 - val_loss: 1.0663e-04 - val_mean_absolute_error: 0.0080
Epoch 82/100
1/126 [..............................] - ETA: 0s - loss: 1.7317e-04 - mean_absolute_error: 0.0100 20/126 [===>..........................] - ETA: 0s - loss: 3.1996e-04 - mean_absolute_error: 0.0136 39/126 [========>.....................] - ETA: 0s - loss: 2.5800e-04 - mean_absolute_error: 0.0122 59/126 [=============>................] - ETA: 0s - loss: 2.4659e-04 - mean_absolute_error: 0.0117 79/126 [=================>............] - ETA: 0s - loss: 2.4350e-04 - mean_absolute_error: 0.0115 98/126 [======================>.......] - ETA: 0s - loss: 2.4348e-04 - mean_absolute_error: 0.0116118/126 [===========================>..] - ETA: 0s - loss: 2.4542e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.4328e-04 - mean_absolute_error: 0.0114 - val_loss: 1.2294e-04 - val_mean_absolute_error: 0.0089
Epoch 83/100
1/126 [..............................] - ETA: 0s - loss: 2.2765e-04 - mean_absolute_error: 0.0121 22/126 [====>.........................] - ETA: 0s - loss: 1.6748e-04 - mean_absolute_error: 0.0096 41/126 [========>.....................] - ETA: 0s - loss: 1.8407e-04 - mean_absolute_error: 0.0097 61/126 [=============>................] - ETA: 0s - loss: 1.9260e-04 - mean_absolute_error: 0.0099 81/126 [==================>...........] - ETA: 0s - loss: 2.0849e-04 - mean_absolute_error: 0.0105100/126 [======================>.......] - ETA: 0s - loss: 2.0622e-04 - mean_absolute_error: 0.0104120/126 [===========================>..] - ETA: 0s - loss: 2.0847e-04 - mean_absolute_error: 0.0104126/126 [==============================] - 0s 3ms/step - loss: 2.0710e-04 - mean_absolute_error: 0.0104 - val_loss: 1.7725e-04 - val_mean_absolute_error: 0.0108
Epoch 84/100
1/126 [..............................] - ETA: 0s - loss: 3.1599e-04 - mean_absolute_error: 0.0136 22/126 [====>.........................] - ETA: 0s - loss: 2.7983e-04 - mean_absolute_error: 0.0124 39/126 [========>.....................] - ETA: 0s - loss: 2.6625e-04 - mean_absolute_error: 0.0122 56/126 [============>.................] - ETA: 0s - loss: 2.4936e-04 - mean_absolute_error: 0.0115 72/126 [================>.............] - ETA: 0s - loss: 2.5123e-04 - mean_absolute_error: 0.0116 88/126 [===================>..........] - ETA: 0s - loss: 2.4991e-04 - mean_absolute_error: 0.0117106/126 [========================>.....] - ETA: 0s - loss: 2.5088e-04 - mean_absolute_error: 0.0117123/126 [============================>.] - ETA: 0s - loss: 2.4201e-04 - mean_absolute_error: 0.0115126/126 [==============================] - 0s 3ms/step - loss: 2.4124e-04 - mean_absolute_error: 0.0115 - val_loss: 1.0206e-04 - val_mean_absolute_error: 0.0078
Epoch 85/100
1/126 [..............................] - ETA: 0s - loss: 1.7082e-04 - mean_absolute_error: 0.0100 21/126 [====>.........................] - ETA: 0s - loss: 1.8663e-04 - mean_absolute_error: 0.0096 41/126 [========>.....................] - ETA: 0s - loss: 2.1398e-04 - mean_absolute_error: 0.0103 61/126 [=============>................] - ETA: 0s - loss: 2.2045e-04 - mean_absolute_error: 0.0104 81/126 [==================>...........] - ETA: 0s - loss: 2.0760e-04 - mean_absolute_error: 0.0102101/126 [=======================>......] - ETA: 0s - loss: 1.9772e-04 - mean_absolute_error: 0.0100121/126 [===========================>..] - ETA: 0s - loss: 2.0090e-04 - mean_absolute_error: 0.0102126/126 [==============================] - 0s 3ms/step - loss: 2.0049e-04 - mean_absolute_error: 0.0102 - val_loss: 1.8553e-04 - val_mean_absolute_error: 0.0111
Epoch 86/100
1/126 [..............................] - ETA: 0s - loss: 4.0013e-04 - mean_absolute_error: 0.0143 21/126 [====>.........................] - ETA: 0s - loss: 2.0692e-04 - mean_absolute_error: 0.0103 41/126 [========>.....................] - ETA: 0s - loss: 1.9425e-04 - mean_absolute_error: 0.0100 61/126 [=============>................] - ETA: 0s - loss: 1.9144e-04 - mean_absolute_error: 0.0100 81/126 [==================>...........] - ETA: 0s - loss: 2.0419e-04 - mean_absolute_error: 0.0105101/126 [=======================>......] - ETA: 0s - loss: 2.0589e-04 - mean_absolute_error: 0.0106122/126 [============================>.] - ETA: 0s - loss: 2.2004e-04 - mean_absolute_error: 0.0109126/126 [==============================] - 0s 3ms/step - loss: 2.2928e-04 - mean_absolute_error: 0.0111 - val_loss: 1.7402e-04 - val_mean_absolute_error: 0.0109
Epoch 87/100
1/126 [..............................] - ETA: 0s - loss: 2.6594e-04 - mean_absolute_error: 0.0132 21/126 [====>.........................] - ETA: 0s - loss: 3.1556e-04 - mean_absolute_error: 0.0137 41/126 [========>.....................] - ETA: 0s - loss: 2.7778e-04 - mean_absolute_error: 0.0126 61/126 [=============>................] - ETA: 0s - loss: 2.5300e-04 - mean_absolute_error: 0.0118 81/126 [==================>...........] - ETA: 0s - loss: 2.4313e-04 - mean_absolute_error: 0.0115101/126 [=======================>......] - ETA: 0s - loss: 2.4289e-04 - mean_absolute_error: 0.0115121/126 [===========================>..] - ETA: 0s - loss: 2.3265e-04 - mean_absolute_error: 0.0111126/126 [==============================] - 0s 3ms/step - loss: 2.2897e-04 - mean_absolute_error: 0.0110 - val_loss: 9.4476e-05 - val_mean_absolute_error: 0.0075
Epoch 88/100
1/126 [..............................] - ETA: 0s - loss: 1.7533e-04 - mean_absolute_error: 0.0097 22/126 [====>.........................] - ETA: 0s - loss: 2.2882e-04 - mean_absolute_error: 0.0119 43/126 [=========>....................] - ETA: 0s - loss: 2.2625e-04 - mean_absolute_error: 0.0113 64/126 [==============>...............] - ETA: 0s - loss: 2.1528e-04 - mean_absolute_error: 0.0108 83/126 [==================>...........] - ETA: 0s - loss: 2.4370e-04 - mean_absolute_error: 0.0115103/126 [=======================>......] - ETA: 0s - loss: 2.5914e-04 - mean_absolute_error: 0.0120123/126 [============================>.] - ETA: 0s - loss: 2.7051e-04 - mean_absolute_error: 0.0123126/126 [==============================] - 0s 3ms/step - loss: 2.6961e-04 - mean_absolute_error: 0.0123 - val_loss: 1.1388e-04 - val_mean_absolute_error: 0.0083
Epoch 89/100
1/126 [..............................] - ETA: 0s - loss: 1.4976e-04 - mean_absolute_error: 0.0095 21/126 [====>.........................] - ETA: 0s - loss: 2.1230e-04 - mean_absolute_error: 0.0106 41/126 [========>.....................] - ETA: 0s - loss: 2.1335e-04 - mean_absolute_error: 0.0106 61/126 [=============>................] - ETA: 0s - loss: 2.0146e-04 - mean_absolute_error: 0.0103 81/126 [==================>...........] - ETA: 0s - loss: 1.9278e-04 - mean_absolute_error: 0.0102101/126 [=======================>......] - ETA: 0s - loss: 2.0424e-04 - mean_absolute_error: 0.0104121/126 [===========================>..] - ETA: 0s - loss: 2.1113e-04 - mean_absolute_error: 0.0105126/126 [==============================] - 0s 3ms/step - loss: 2.1051e-04 - mean_absolute_error: 0.0106 - val_loss: 2.2319e-04 - val_mean_absolute_error: 0.0126
Epoch 90/100
1/126 [..............................] - ETA: 0s - loss: 2.2364e-04 - mean_absolute_error: 0.0122 21/126 [====>.........................] - ETA: 0s - loss: 2.3002e-04 - mean_absolute_error: 0.0114 41/126 [========>.....................] - ETA: 0s - loss: 2.7917e-04 - mean_absolute_error: 0.0127 61/126 [=============>................] - ETA: 0s - loss: 2.5446e-04 - mean_absolute_error: 0.0120 74/126 [================>.............] - ETA: 0s - loss: 2.4305e-04 - mean_absolute_error: 0.0116 90/126 [====================>.........] - ETA: 0s - loss: 2.3218e-04 - mean_absolute_error: 0.0114107/126 [========================>.....] - ETA: 0s - loss: 2.2755e-04 - mean_absolute_error: 0.0113124/126 [============================>.] - ETA: 0s - loss: 2.3403e-04 - mean_absolute_error: 0.0113126/126 [==============================] - 0s 3ms/step - loss: 2.3309e-04 - mean_absolute_error: 0.0113 - val_loss: 9.4013e-05 - val_mean_absolute_error: 0.0075
Epoch 91/100
1/126 [..............................] - ETA: 0s - loss: 9.1687e-05 - mean_absolute_error: 0.0072 20/126 [===>..........................] - ETA: 0s - loss: 1.6097e-04 - mean_absolute_error: 0.0097 40/126 [========>.....................] - ETA: 0s - loss: 2.1409e-04 - mean_absolute_error: 0.0109 60/126 [=============>................] - ETA: 0s - loss: 2.1954e-04 - mean_absolute_error: 0.0107 80/126 [==================>...........] - ETA: 0s - loss: 2.1684e-04 - mean_absolute_error: 0.0106100/126 [======================>.......] - ETA: 0s - loss: 2.0720e-04 - mean_absolute_error: 0.0104119/126 [===========================>..] - ETA: 0s - loss: 2.0399e-04 - mean_absolute_error: 0.0104126/126 [==============================] - 0s 3ms/step - loss: 2.0556e-04 - mean_absolute_error: 0.0104 - val_loss: 1.0344e-04 - val_mean_absolute_error: 0.0079
Epoch 92/100
1/126 [..............................] - ETA: 0s - loss: 2.1307e-04 - mean_absolute_error: 0.0113 21/126 [====>.........................] - ETA: 0s - loss: 2.1543e-04 - mean_absolute_error: 0.0102 41/126 [========>.....................] - ETA: 0s - loss: 1.9157e-04 - mean_absolute_error: 0.0100 61/126 [=============>................] - ETA: 0s - loss: 1.8874e-04 - mean_absolute_error: 0.0100 80/126 [==================>...........] - ETA: 0s - loss: 1.9000e-04 - mean_absolute_error: 0.0099100/126 [======================>.......] - ETA: 0s - loss: 1.9394e-04 - mean_absolute_error: 0.0100119/126 [===========================>..] - ETA: 0s - loss: 1.9100e-04 - mean_absolute_error: 0.0100126/126 [==============================] - 0s 3ms/step - loss: 1.9315e-04 - mean_absolute_error: 0.0100 - val_loss: 2.6765e-04 - val_mean_absolute_error: 0.0140
Epoch 93/100
1/126 [..............................] - ETA: 0s - loss: 5.5318e-04 - mean_absolute_error: 0.0187 21/126 [====>.........................] - ETA: 0s - loss: 2.5696e-04 - mean_absolute_error: 0.0118 41/126 [========>.....................] - ETA: 0s - loss: 2.1802e-04 - mean_absolute_error: 0.0106 61/126 [=============>................] - ETA: 0s - loss: 2.1858e-04 - mean_absolute_error: 0.0107 81/126 [==================>...........] - ETA: 0s - loss: 2.3627e-04 - mean_absolute_error: 0.0113101/126 [=======================>......] - ETA: 0s - loss: 2.4562e-04 - mean_absolute_error: 0.0116120/126 [===========================>..] - ETA: 0s - loss: 2.4501e-04 - mean_absolute_error: 0.0117126/126 [==============================] - 0s 3ms/step - loss: 2.4937e-04 - mean_absolute_error: 0.0118 - val_loss: 2.3444e-04 - val_mean_absolute_error: 0.0130
Epoch 94/100
1/126 [..............................] - ETA: 0s - loss: 2.4906e-04 - mean_absolute_error: 0.0120 21/126 [====>.........................] - ETA: 0s - loss: 2.4251e-04 - mean_absolute_error: 0.0119 41/126 [========>.....................] - ETA: 0s - loss: 2.2405e-04 - mean_absolute_error: 0.0111 61/126 [=============>................] - ETA: 0s - loss: 2.0951e-04 - mean_absolute_error: 0.0107 80/126 [==================>...........] - ETA: 0s - loss: 2.1006e-04 - mean_absolute_error: 0.0105100/126 [======================>.......] - ETA: 0s - loss: 2.0860e-04 - mean_absolute_error: 0.0105120/126 [===========================>..] - ETA: 0s - loss: 2.0554e-04 - mean_absolute_error: 0.0104126/126 [==============================] - 0s 3ms/step - loss: 2.0565e-04 - mean_absolute_error: 0.0104 - val_loss: 1.3073e-04 - val_mean_absolute_error: 0.0093
Epoch 95/100
1/126 [..............................] - ETA: 0s - loss: 3.7440e-04 - mean_absolute_error: 0.0125 21/126 [====>.........................] - ETA: 0s - loss: 2.1293e-04 - mean_absolute_error: 0.0110 41/126 [========>.....................] - ETA: 0s - loss: 2.1031e-04 - mean_absolute_error: 0.0109 62/126 [=============>................] - ETA: 0s - loss: 1.9350e-04 - mean_absolute_error: 0.0104 82/126 [==================>...........] - ETA: 0s - loss: 1.8551e-04 - mean_absolute_error: 0.0102102/126 [=======================>......] - ETA: 0s - loss: 2.0260e-04 - mean_absolute_error: 0.0104122/126 [============================>.] - ETA: 0s - loss: 2.1004e-04 - mean_absolute_error: 0.0105126/126 [==============================] - 0s 3ms/step - loss: 2.0864e-04 - mean_absolute_error: 0.0105 - val_loss: 1.1927e-04 - val_mean_absolute_error: 0.0086
Epoch 96/100
1/126 [..............................] - ETA: 0s - loss: 2.5539e-04 - mean_absolute_error: 0.0121 21/126 [====>.........................] - ETA: 0s - loss: 1.9575e-04 - mean_absolute_error: 0.0107 41/126 [========>.....................] - ETA: 0s - loss: 2.0145e-04 - mean_absolute_error: 0.0104 61/126 [=============>................] - ETA: 0s - loss: 2.0585e-04 - mean_absolute_error: 0.0105 81/126 [==================>...........] - ETA: 0s - loss: 2.0818e-04 - mean_absolute_error: 0.0105101/126 [=======================>......] - ETA: 0s - loss: 2.0895e-04 - mean_absolute_error: 0.0105122/126 [============================>.] - ETA: 0s - loss: 2.0212e-04 - mean_absolute_error: 0.0103126/126 [==============================] - 0s 3ms/step - loss: 2.0008e-04 - mean_absolute_error: 0.0103 - val_loss: 9.8344e-05 - val_mean_absolute_error: 0.0077
Epoch 97/100
1/126 [..............................] - ETA: 0s - loss: 1.0717e-04 - mean_absolute_error: 0.0073 21/126 [====>.........................] - ETA: 0s - loss: 1.6062e-04 - mean_absolute_error: 0.0091 41/126 [========>.....................] - ETA: 0s - loss: 1.6723e-04 - mean_absolute_error: 0.0094 61/126 [=============>................] - ETA: 0s - loss: 1.8728e-04 - mean_absolute_error: 0.0096 81/126 [==================>...........] - ETA: 0s - loss: 1.8198e-04 - mean_absolute_error: 0.0096101/126 [=======================>......] - ETA: 0s - loss: 1.9497e-04 - mean_absolute_error: 0.0099121/126 [===========================>..] - ETA: 0s - loss: 1.9462e-04 - mean_absolute_error: 0.0100126/126 [==============================] - 0s 3ms/step - loss: 1.9601e-04 - mean_absolute_error: 0.0100 - val_loss: 3.0494e-04 - val_mean_absolute_error: 0.0152
Epoch 98/100
1/126 [..............................] - ETA: 0s - loss: 3.0500e-04 - mean_absolute_error: 0.0152 21/126 [====>.........................] - ETA: 0s - loss: 1.7951e-04 - mean_absolute_error: 0.0102 41/126 [========>.....................] - ETA: 0s - loss: 2.0623e-04 - mean_absolute_error: 0.0105 61/126 [=============>................] - ETA: 0s - loss: 1.9427e-04 - mean_absolute_error: 0.0102 81/126 [==================>...........] - ETA: 0s - loss: 2.0900e-04 - mean_absolute_error: 0.0106101/126 [=======================>......] - ETA: 0s - loss: 2.1710e-04 - mean_absolute_error: 0.0108121/126 [===========================>..] - ETA: 0s - loss: 2.1707e-04 - mean_absolute_error: 0.0107126/126 [==============================] - 0s 3ms/step - loss: 2.1507e-04 - mean_absolute_error: 0.0106 - val_loss: 9.3229e-05 - val_mean_absolute_error: 0.0074
Epoch 99/100
1/126 [..............................] - ETA: 0s - loss: 2.0405e-04 - mean_absolute_error: 0.0112 21/126 [====>.........................] - ETA: 0s - loss: 2.2018e-04 - mean_absolute_error: 0.0110 41/126 [========>.....................] - ETA: 0s - loss: 2.2528e-04 - mean_absolute_error: 0.0110 61/126 [=============>................] - ETA: 0s - loss: 2.0160e-04 - mean_absolute_error: 0.0102 81/126 [==================>...........] - ETA: 0s - loss: 1.9442e-04 - mean_absolute_error: 0.0100101/126 [=======================>......] - ETA: 0s - loss: 1.9448e-04 - mean_absolute_error: 0.0101121/126 [===========================>..] - ETA: 0s - loss: 1.9926e-04 - mean_absolute_error: 0.0102126/126 [==============================] - 0s 3ms/step - loss: 1.9831e-04 - mean_absolute_error: 0.0102 - val_loss: 1.4582e-04 - val_mean_absolute_error: 0.0099
Epoch 100/100
1/126 [..............................] - ETA: 0s - loss: 1.1874e-04 - mean_absolute_error: 0.0090 21/126 [====>.........................] - ETA: 0s - loss: 1.4859e-04 - mean_absolute_error: 0.0094 42/126 [=========>....................] - ETA: 0s - loss: 1.8721e-04 - mean_absolute_error: 0.0102 62/126 [=============>................] - ETA: 0s - loss: 1.8726e-04 - mean_absolute_error: 0.0103 82/126 [==================>...........] - ETA: 0s - loss: 2.0121e-04 - mean_absolute_error: 0.0105102/126 [=======================>......] - ETA: 0s - loss: 2.1178e-04 - mean_absolute_error: 0.0106122/126 [============================>.] - ETA: 0s - loss: 2.0533e-04 - mean_absolute_error: 0.0104126/126 [==============================] - 0s 3ms/step - loss: 2.0366e-04 - mean_absolute_error: 0.0103 - val_loss: 9.0787e-05 - val_mean_absolute_error: 0.0073
<keras.src.callbacks.History at 0x1b9a2801ad0>
After the training and fitting of the Machine Learning model for Austrailia, I tried to create visualizations comparing the model against the country’s training dataset, validation dataset, but most importantly the testing dataset (as shown below in the line graphs). Note that the darker and thicker blue lines represent the prediction model’s projections and the thinner red lines is the observed/gathered data.
```{python}
# Testing the Machine Learning Model prediction for Austrailia with the train,
# validation, and test sets
# Most important is the test set prediction as this tests the effectiveness
# of the Machine Learning model on data it has not seen before
austrailia_train_pred = austrailia_model.predict(X_austrailia_train).flatten()
plt.plot(dates_austrailia_train, austrailia_train_pred, linewidth=4)
plt.plot(dates_austrailia_train, y_austrailia_train, linewidth=1)
plt.legend(["Training Predictions", "Training Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Austrailia - Training Set Predictions vs. Observations")
plt.show()
austrailia_val_pred = austrailia_model.predict(X_austrailia_val).flatten()
plt.plot(dates_austrailia_val, austrailia_val_pred, linewidth=4)
plt.plot(dates_austrailia_val, y_austrailia_val, linewidth=1)
plt.legend(["Validation Predictions", "Validation Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Austrailia - Validation Set Predictions vs. Observations")
plt.show()
austrailia_test_pred = austrailia_model.predict(X_austrailia_test).flatten()
plt.plot(dates_austrailia_test, austrailia_test_pred, linewidth=4)
plt.plot(dates_austrailia_test, y_austrailia_test, linewidth=1)
plt.legend(["Testing Predictions", "Testing Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Austrailia - Testing Set Predictions vs. Observations")
plt.show()
``` 1/126 [..............................] - ETA: 43s 40/126 [========>.....................] - ETA: 0s 77/126 [=================>............] - ETA: 0s116/126 [==========================>...] - ETA: 0s126/126 [==============================] - 1s 1ms/step
1/16 [>.............................] - ETA: 0s16/16 [==============================] - 0s 1ms/step
1/16 [>.............................] - ETA: 0s16/16 [==============================] - 0s 1ms/step
Through careful consideration of all of the prediction-based vs. observation-based contrast visualizations together, I consolidated all of graphics into one singular visualization for you to see below to get a more general perspective of the effectiveness of the Machine Learning model at training and fitting towards predicting Austrailia’s international currency rate with the United States.
```{python}
# Plotting Austrailia's observational (reference) data with the predictions of
# its Machine Learning Model (as a way to visually inspect the effectiveness of
# the model)
plt.plot(dates_austrailia_train, austrailia_train_pred, linewidth=4)
plt.plot(dates_austrailia_train, y_austrailia_train, linewidth=1)
plt.plot(dates_austrailia_val, austrailia_val_pred, linewidth=4)
plt.plot(dates_austrailia_val, y_austrailia_val, linewidth=1)
plt.plot(dates_austrailia_test, austrailia_test_pred, linewidth=4)
plt.plot(dates_austrailia_test, y_austrailia_test, linewidth=1)
plt.legend(["Training Predictions",
"Training Observations",
"Validation Predictions",
"Validation Observations",
"Testing Predictions",
"Testing Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Culmination of the Three Machine Learning Phases of Austrailia's Dataset - Predictions vs. Observations")
plt.show()
```Once Austraila’s data was completely trained and visualized, I worked on Canada’s data (as shown below):
Since the data (date, X, and y) is split into three np.arrays and to be more efficient, I will manually split Canada’s data into train, test, and validation datasets for the Machine Learning model with 80% going to the training dataset, the next 10% going to the validation dataset, and the last 10% going to the test dataset for each np.array respectively.
```{python}
# Splitting Canada's data into train, test, and validation sets on 3 mediums:
# the X-axis, the y-axis, and the indices (represented by dates)
dates_canada_train, X_canada_train, y_canada_train = dates_canada[:percentile_80], X_canada[:percentile_80], y_canada[:percentile_80]
dates_canada_val, X_canada_val, y_canada_val = dates_canada[percentile_80:percentile_90], X_canada[percentile_80:percentile_90], y_canada[percentile_80:percentile_90]
dates_canada_test, X_canada_test, y_canada_test = dates_canada[percentile_90:], X_canada[percentile_90:], y_canada[percentile_90:]
plt.plot(dates_canada_train, y_canada_train, linewidth=1)
plt.plot(dates_canada_val, y_canada_val, linewidth=1)
plt.plot(dates_canada_test, y_canada_test, linewidth=1)
plt.legend(["Training", "Validation", "Testing"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Split of Canada's Data for LSTM Model")
plt.show()
```Now, I began to configure the Machine Learning model. We added Sequential layers: an Input layer 3 by 1 because we will have 3 np.arrays of Input and 1 np.array as output, utilize a LSTM (Long Short-Term Memory) layer of 64 neurons, apply 2 levels of dense layers with 32 neurons and folliowing recommendations online to use the RELU (Rectified Linear Unit) Activiation Function, and I followed up with one last dense layer of 1 neuron as our output layer since we are just trying to linearly-predict the next currency-rate on a near-future date. Once I configured the Sequential layers, we are ready to compile the model, utilzing the mean_square_error as our minimizing loss function, using the Adam optimizer, and comparing our trained model against our data with the mean_absolute_error metric. Lastly, I fitted our model, utilzing our X_train and Y_train datasets for fitting with validation from our X_valid and Y_valid datasets at 100 epochs.
```{python}
# Configuring the Machine Learning Tensorflow Model for Canada
canada_model = Sequential([layers.Input((3, 1)),
layers.LSTM(64),
layers.Dense(32, activation="relu"),
layers.Dense(32, activation="relu"),
layers.Dense(1)])
canada_model.compile(loss="mse",
optimizer=Adam(learning_rate=0.001),
metrics=["mean_absolute_error"])
canada_model.fit(X_canada_train, y_canada_train, validation_data=(X_canada_val, y_canada_val), epochs=100)
```Epoch 1/100
1/126 [..............................] - ETA: 3:48 - loss: 1.6084 - mean_absolute_error: 1.2506 22/126 [====>.........................] - ETA: 0s - loss: 1.0615 - mean_absolute_error: 1.0062 42/126 [=========>....................] - ETA: 0s - loss: 0.6235 - mean_absolute_error: 0.6737 62/126 [=============>................] - ETA: 0s - loss: 0.4284 - mean_absolute_error: 0.4923 82/126 [==================>...........] - ETA: 0s - loss: 0.3249 - mean_absolute_error: 0.3852102/126 [=======================>......] - ETA: 0s - loss: 0.2617 - mean_absolute_error: 0.3184122/126 [============================>.] - ETA: 0s - loss: 0.2192 - mean_absolute_error: 0.2734126/126 [==============================] - 3s 6ms/step - loss: 0.2134 - mean_absolute_error: 0.2671 - val_loss: 3.5847e-04 - val_mean_absolute_error: 0.0153
Epoch 2/100
1/126 [..............................] - ETA: 0s - loss: 0.0024 - mean_absolute_error: 0.0433 24/126 [====>.........................] - ETA: 0s - loss: 0.0022 - mean_absolute_error: 0.0410 45/126 [=========>....................] - ETA: 0s - loss: 0.0021 - mean_absolute_error: 0.0396 67/126 [==============>...............] - ETA: 0s - loss: 0.0019 - mean_absolute_error: 0.0385 87/126 [===================>..........] - ETA: 0s - loss: 0.0018 - mean_absolute_error: 0.0373108/126 [========================>.....] - ETA: 0s - loss: 0.0017 - mean_absolute_error: 0.0357126/126 [==============================] - 0s 3ms/step - loss: 0.0016 - mean_absolute_error: 0.0346 - val_loss: 2.1387e-04 - val_mean_absolute_error: 0.0116
Epoch 3/100
1/126 [..............................] - ETA: 0s - loss: 9.9135e-04 - mean_absolute_error: 0.0287 22/126 [====>.........................] - ETA: 0s - loss: 9.3043e-04 - mean_absolute_error: 0.0266 42/126 [=========>....................] - ETA: 0s - loss: 8.5092e-04 - mean_absolute_error: 0.0254 62/126 [=============>................] - ETA: 0s - loss: 7.8749e-04 - mean_absolute_error: 0.0243 83/126 [==================>...........] - ETA: 0s - loss: 7.3721e-04 - mean_absolute_error: 0.0235104/126 [=======================>......] - ETA: 0s - loss: 6.7967e-04 - mean_absolute_error: 0.0224125/126 [============================>.] - ETA: 0s - loss: 6.2588e-04 - mean_absolute_error: 0.0214126/126 [==============================] - 0s 3ms/step - loss: 6.2518e-04 - mean_absolute_error: 0.0214 - val_loss: 2.0174e-04 - val_mean_absolute_error: 0.0116
Epoch 4/100
1/126 [..............................] - ETA: 0s - loss: 3.3846e-04 - mean_absolute_error: 0.0154 22/126 [====>.........................] - ETA: 0s - loss: 3.0800e-04 - mean_absolute_error: 0.0147 43/126 [=========>....................] - ETA: 0s - loss: 2.8997e-04 - mean_absolute_error: 0.0142 63/126 [==============>...............] - ETA: 0s - loss: 2.7068e-04 - mean_absolute_error: 0.0137 83/126 [==================>...........] - ETA: 0s - loss: 2.5336e-04 - mean_absolute_error: 0.0132104/126 [=======================>......] - ETA: 0s - loss: 2.3448e-04 - mean_absolute_error: 0.0126125/126 [============================>.] - ETA: 0s - loss: 2.1899e-04 - mean_absolute_error: 0.0121126/126 [==============================] - 0s 3ms/step - loss: 2.1865e-04 - mean_absolute_error: 0.0121 - val_loss: 1.2445e-04 - val_mean_absolute_error: 0.0089
Epoch 5/100
1/126 [..............................] - ETA: 0s - loss: 1.2998e-04 - mean_absolute_error: 0.0093 22/126 [====>.........................] - ETA: 0s - loss: 1.3957e-04 - mean_absolute_error: 0.0094 43/126 [=========>....................] - ETA: 0s - loss: 1.3502e-04 - mean_absolute_error: 0.0092 63/126 [==============>...............] - ETA: 0s - loss: 1.2710e-04 - mean_absolute_error: 0.0088 84/126 [===================>..........] - ETA: 0s - loss: 1.2479e-04 - mean_absolute_error: 0.0087104/126 [=======================>......] - ETA: 0s - loss: 1.2176e-04 - mean_absolute_error: 0.0086124/126 [============================>.] - ETA: 0s - loss: 1.1886e-04 - mean_absolute_error: 0.0085126/126 [==============================] - 0s 3ms/step - loss: 1.1853e-04 - mean_absolute_error: 0.0084 - val_loss: 1.2393e-04 - val_mean_absolute_error: 0.0088
Epoch 6/100
1/126 [..............................] - ETA: 0s - loss: 1.1553e-04 - mean_absolute_error: 0.0085 22/126 [====>.........................] - ETA: 0s - loss: 9.7265e-05 - mean_absolute_error: 0.0076 43/126 [=========>....................] - ETA: 0s - loss: 9.8758e-05 - mean_absolute_error: 0.0077 63/126 [==============>...............] - ETA: 0s - loss: 9.9929e-05 - mean_absolute_error: 0.0076 83/126 [==================>...........] - ETA: 0s - loss: 1.0241e-04 - mean_absolute_error: 0.0077101/126 [=======================>......] - ETA: 0s - loss: 1.0484e-04 - mean_absolute_error: 0.0078120/126 [===========================>..] - ETA: 0s - loss: 1.0564e-04 - mean_absolute_error: 0.0078126/126 [==============================] - 0s 3ms/step - loss: 1.0605e-04 - mean_absolute_error: 0.0079 - val_loss: 1.1293e-04 - val_mean_absolute_error: 0.0083
Epoch 7/100
1/126 [..............................] - ETA: 0s - loss: 5.3353e-05 - mean_absolute_error: 0.0061 21/126 [====>.........................] - ETA: 0s - loss: 1.1539e-04 - mean_absolute_error: 0.0080 40/126 [========>.....................] - ETA: 0s - loss: 1.0610e-04 - mean_absolute_error: 0.0077 60/126 [=============>................] - ETA: 0s - loss: 1.0095e-04 - mean_absolute_error: 0.0076 80/126 [==================>...........] - ETA: 0s - loss: 1.0207e-04 - mean_absolute_error: 0.0076101/126 [=======================>......] - ETA: 0s - loss: 1.0487e-04 - mean_absolute_error: 0.0078122/126 [============================>.] - ETA: 0s - loss: 1.0330e-04 - mean_absolute_error: 0.0077126/126 [==============================] - 0s 3ms/step - loss: 1.0288e-04 - mean_absolute_error: 0.0077 - val_loss: 1.1638e-04 - val_mean_absolute_error: 0.0085
Epoch 8/100
1/126 [..............................] - ETA: 0s - loss: 1.1347e-04 - mean_absolute_error: 0.0079 21/126 [====>.........................] - ETA: 0s - loss: 1.0499e-04 - mean_absolute_error: 0.0079 41/126 [========>.....................] - ETA: 0s - loss: 9.8606e-05 - mean_absolute_error: 0.0077 62/126 [=============>................] - ETA: 0s - loss: 9.9099e-05 - mean_absolute_error: 0.0076 83/126 [==================>...........] - ETA: 0s - loss: 1.0490e-04 - mean_absolute_error: 0.0078104/126 [=======================>......] - ETA: 0s - loss: 1.0291e-04 - mean_absolute_error: 0.0077124/126 [============================>.] - ETA: 0s - loss: 1.0185e-04 - mean_absolute_error: 0.0077126/126 [==============================] - 0s 3ms/step - loss: 1.0129e-04 - mean_absolute_error: 0.0076 - val_loss: 1.1290e-04 - val_mean_absolute_error: 0.0081
Epoch 9/100
1/126 [..............................] - ETA: 0s - loss: 1.0115e-04 - mean_absolute_error: 0.0087 22/126 [====>.........................] - ETA: 0s - loss: 9.5266e-05 - mean_absolute_error: 0.0075 42/126 [=========>....................] - ETA: 0s - loss: 1.0179e-04 - mean_absolute_error: 0.0077 63/126 [==============>...............] - ETA: 0s - loss: 1.0233e-04 - mean_absolute_error: 0.0077 84/126 [===================>..........] - ETA: 0s - loss: 1.0381e-04 - mean_absolute_error: 0.0077104/126 [=======================>......] - ETA: 0s - loss: 1.0333e-04 - mean_absolute_error: 0.0077125/126 [============================>.] - ETA: 0s - loss: 1.0072e-04 - mean_absolute_error: 0.0076126/126 [==============================] - 0s 3ms/step - loss: 1.0051e-04 - mean_absolute_error: 0.0076 - val_loss: 1.3586e-04 - val_mean_absolute_error: 0.0093
Epoch 10/100
1/126 [..............................] - ETA: 0s - loss: 1.2833e-04 - mean_absolute_error: 0.0090 22/126 [====>.........................] - ETA: 0s - loss: 1.1013e-04 - mean_absolute_error: 0.0079 43/126 [=========>....................] - ETA: 0s - loss: 1.0653e-04 - mean_absolute_error: 0.0079 63/126 [==============>...............] - ETA: 0s - loss: 1.0563e-04 - mean_absolute_error: 0.0078 84/126 [===================>..........] - ETA: 0s - loss: 1.0711e-04 - mean_absolute_error: 0.0078105/126 [========================>.....] - ETA: 0s - loss: 1.0514e-04 - mean_absolute_error: 0.0078126/126 [==============================] - ETA: 0s - loss: 1.0370e-04 - mean_absolute_error: 0.0077126/126 [==============================] - 0s 3ms/step - loss: 1.0370e-04 - mean_absolute_error: 0.0077 - val_loss: 1.5492e-04 - val_mean_absolute_error: 0.0100
Epoch 11/100
1/126 [..............................] - ETA: 0s - loss: 1.1092e-04 - mean_absolute_error: 0.0085 22/126 [====>.........................] - ETA: 0s - loss: 9.8273e-05 - mean_absolute_error: 0.0076 43/126 [=========>....................] - ETA: 0s - loss: 9.2782e-05 - mean_absolute_error: 0.0074 64/126 [==============>...............] - ETA: 0s - loss: 9.4671e-05 - mean_absolute_error: 0.0074 84/126 [===================>..........] - ETA: 0s - loss: 9.8771e-05 - mean_absolute_error: 0.0075104/126 [=======================>......] - ETA: 0s - loss: 1.0227e-04 - mean_absolute_error: 0.0076124/126 [============================>.] - ETA: 0s - loss: 1.0316e-04 - mean_absolute_error: 0.0077126/126 [==============================] - 0s 3ms/step - loss: 1.0292e-04 - mean_absolute_error: 0.0077 - val_loss: 1.1871e-04 - val_mean_absolute_error: 0.0086
Epoch 12/100
1/126 [..............................] - ETA: 0s - loss: 9.1325e-05 - mean_absolute_error: 0.0069 22/126 [====>.........................] - ETA: 0s - loss: 1.1217e-04 - mean_absolute_error: 0.0077 43/126 [=========>....................] - ETA: 0s - loss: 1.0369e-04 - mean_absolute_error: 0.0075 64/126 [==============>...............] - ETA: 0s - loss: 1.0422e-04 - mean_absolute_error: 0.0076 84/126 [===================>..........] - ETA: 0s - loss: 1.0408e-04 - mean_absolute_error: 0.0076104/126 [=======================>......] - ETA: 0s - loss: 1.0276e-04 - mean_absolute_error: 0.0076124/126 [============================>.] - ETA: 0s - loss: 1.0061e-04 - mean_absolute_error: 0.0075126/126 [==============================] - 0s 3ms/step - loss: 1.0042e-04 - mean_absolute_error: 0.0075 - val_loss: 1.2555e-04 - val_mean_absolute_error: 0.0089
Epoch 13/100
1/126 [..............................] - ETA: 0s - loss: 7.2034e-05 - mean_absolute_error: 0.0065 22/126 [====>.........................] - ETA: 0s - loss: 1.0719e-04 - mean_absolute_error: 0.0077 43/126 [=========>....................] - ETA: 0s - loss: 1.0976e-04 - mean_absolute_error: 0.0078 63/126 [==============>...............] - ETA: 0s - loss: 1.1095e-04 - mean_absolute_error: 0.0079 82/126 [==================>...........] - ETA: 0s - loss: 1.0971e-04 - mean_absolute_error: 0.0079103/126 [=======================>......] - ETA: 0s - loss: 1.0986e-04 - mean_absolute_error: 0.0079124/126 [============================>.] - ETA: 0s - loss: 1.0692e-04 - mean_absolute_error: 0.0078126/126 [==============================] - 0s 3ms/step - loss: 1.0678e-04 - mean_absolute_error: 0.0078 - val_loss: 1.1227e-04 - val_mean_absolute_error: 0.0081
Epoch 14/100
1/126 [..............................] - ETA: 0s - loss: 8.3271e-05 - mean_absolute_error: 0.0074 22/126 [====>.........................] - ETA: 0s - loss: 1.1535e-04 - mean_absolute_error: 0.0086 43/126 [=========>....................] - ETA: 0s - loss: 1.1124e-04 - mean_absolute_error: 0.0082 63/126 [==============>...............] - ETA: 0s - loss: 1.0562e-04 - mean_absolute_error: 0.0079 84/126 [===================>..........] - ETA: 0s - loss: 1.0476e-04 - mean_absolute_error: 0.0079105/126 [========================>.....] - ETA: 0s - loss: 1.0693e-04 - mean_absolute_error: 0.0079124/126 [============================>.] - ETA: 0s - loss: 1.0703e-04 - mean_absolute_error: 0.0079126/126 [==============================] - 0s 3ms/step - loss: 1.0769e-04 - mean_absolute_error: 0.0079 - val_loss: 1.1415e-04 - val_mean_absolute_error: 0.0084
Epoch 15/100
1/126 [..............................] - ETA: 0s - loss: 7.8001e-05 - mean_absolute_error: 0.0065 22/126 [====>.........................] - ETA: 0s - loss: 1.0325e-04 - mean_absolute_error: 0.0077 42/126 [=========>....................] - ETA: 0s - loss: 1.1015e-04 - mean_absolute_error: 0.0079 62/126 [=============>................] - ETA: 0s - loss: 1.1069e-04 - mean_absolute_error: 0.0080 82/126 [==================>...........] - ETA: 0s - loss: 1.1093e-04 - mean_absolute_error: 0.0079102/126 [=======================>......] - ETA: 0s - loss: 1.1017e-04 - mean_absolute_error: 0.0079122/126 [============================>.] - ETA: 0s - loss: 1.0892e-04 - mean_absolute_error: 0.0079126/126 [==============================] - 0s 3ms/step - loss: 1.0878e-04 - mean_absolute_error: 0.0079 - val_loss: 1.4823e-04 - val_mean_absolute_error: 0.0098
Epoch 16/100
1/126 [..............................] - ETA: 0s - loss: 9.0254e-05 - mean_absolute_error: 0.0066 22/126 [====>.........................] - ETA: 0s - loss: 1.3303e-04 - mean_absolute_error: 0.0081 42/126 [=========>....................] - ETA: 0s - loss: 1.1483e-04 - mean_absolute_error: 0.0079 62/126 [=============>................] - ETA: 0s - loss: 1.0904e-04 - mean_absolute_error: 0.0077 82/126 [==================>...........] - ETA: 0s - loss: 1.0511e-04 - mean_absolute_error: 0.0076102/126 [=======================>......] - ETA: 0s - loss: 1.0262e-04 - mean_absolute_error: 0.0076122/126 [============================>.] - ETA: 0s - loss: 1.0312e-04 - mean_absolute_error: 0.0076126/126 [==============================] - 0s 3ms/step - loss: 1.0332e-04 - mean_absolute_error: 0.0077 - val_loss: 1.2676e-04 - val_mean_absolute_error: 0.0089
Epoch 17/100
1/126 [..............................] - ETA: 0s - loss: 8.8973e-05 - mean_absolute_error: 0.0072 21/126 [====>.........................] - ETA: 0s - loss: 9.2767e-05 - mean_absolute_error: 0.0073 41/126 [========>.....................] - ETA: 0s - loss: 1.0424e-04 - mean_absolute_error: 0.0077 61/126 [=============>................] - ETA: 0s - loss: 1.0381e-04 - mean_absolute_error: 0.0077 81/126 [==================>...........] - ETA: 0s - loss: 1.0062e-04 - mean_absolute_error: 0.0076101/126 [=======================>......] - ETA: 0s - loss: 9.9393e-05 - mean_absolute_error: 0.0076122/126 [============================>.] - ETA: 0s - loss: 1.0245e-04 - mean_absolute_error: 0.0077126/126 [==============================] - 0s 3ms/step - loss: 1.0358e-04 - mean_absolute_error: 0.0077 - val_loss: 1.1147e-04 - val_mean_absolute_error: 0.0081
Epoch 18/100
1/126 [..............................] - ETA: 0s - loss: 7.8883e-05 - mean_absolute_error: 0.0072 22/126 [====>.........................] - ETA: 0s - loss: 1.1179e-04 - mean_absolute_error: 0.0081 42/126 [=========>....................] - ETA: 0s - loss: 1.0870e-04 - mean_absolute_error: 0.0079 62/126 [=============>................] - ETA: 0s - loss: 1.1225e-04 - mean_absolute_error: 0.0081 83/126 [==================>...........] - ETA: 0s - loss: 1.1220e-04 - mean_absolute_error: 0.0081104/126 [=======================>......] - ETA: 0s - loss: 1.1102e-04 - mean_absolute_error: 0.0080125/126 [============================>.] - ETA: 0s - loss: 1.1023e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.1022e-04 - mean_absolute_error: 0.0080 - val_loss: 1.4748e-04 - val_mean_absolute_error: 0.0098
Epoch 19/100
1/126 [..............................] - ETA: 0s - loss: 1.4576e-04 - mean_absolute_error: 0.0092 22/126 [====>.........................] - ETA: 0s - loss: 1.0922e-04 - mean_absolute_error: 0.0078 43/126 [=========>....................] - ETA: 0s - loss: 1.0496e-04 - mean_absolute_error: 0.0078 64/126 [==============>...............] - ETA: 0s - loss: 1.0795e-04 - mean_absolute_error: 0.0078 84/126 [===================>..........] - ETA: 0s - loss: 1.0862e-04 - mean_absolute_error: 0.0079104/126 [=======================>......] - ETA: 0s - loss: 1.0824e-04 - mean_absolute_error: 0.0079123/126 [============================>.] - ETA: 0s - loss: 1.0854e-04 - mean_absolute_error: 0.0079126/126 [==============================] - 0s 3ms/step - loss: 1.0854e-04 - mean_absolute_error: 0.0080 - val_loss: 1.2748e-04 - val_mean_absolute_error: 0.0089
Epoch 20/100
1/126 [..............................] - ETA: 0s - loss: 9.1216e-05 - mean_absolute_error: 0.0075 21/126 [====>.........................] - ETA: 0s - loss: 1.2056e-04 - mean_absolute_error: 0.0084 41/126 [========>.....................] - ETA: 0s - loss: 1.1634e-04 - mean_absolute_error: 0.0082 61/126 [=============>................] - ETA: 0s - loss: 1.1394e-04 - mean_absolute_error: 0.0081 82/126 [==================>...........] - ETA: 0s - loss: 1.1147e-04 - mean_absolute_error: 0.0080102/126 [=======================>......] - ETA: 0s - loss: 1.0956e-04 - mean_absolute_error: 0.0079122/126 [============================>.] - ETA: 0s - loss: 1.0885e-04 - mean_absolute_error: 0.0079126/126 [==============================] - 0s 3ms/step - loss: 1.0878e-04 - mean_absolute_error: 0.0079 - val_loss: 1.3094e-04 - val_mean_absolute_error: 0.0091
Epoch 21/100
1/126 [..............................] - ETA: 0s - loss: 5.7664e-05 - mean_absolute_error: 0.0064 21/126 [====>.........................] - ETA: 0s - loss: 9.4649e-05 - mean_absolute_error: 0.0076 42/126 [=========>....................] - ETA: 0s - loss: 9.7874e-05 - mean_absolute_error: 0.0077 63/126 [==============>...............] - ETA: 0s - loss: 1.0093e-04 - mean_absolute_error: 0.0077 84/126 [===================>..........] - ETA: 0s - loss: 1.0268e-04 - mean_absolute_error: 0.0077105/126 [========================>.....] - ETA: 0s - loss: 1.0708e-04 - mean_absolute_error: 0.0079125/126 [============================>.] - ETA: 0s - loss: 1.0808e-04 - mean_absolute_error: 0.0079126/126 [==============================] - 0s 3ms/step - loss: 1.0804e-04 - mean_absolute_error: 0.0079 - val_loss: 1.2977e-04 - val_mean_absolute_error: 0.0091
Epoch 22/100
1/126 [..............................] - ETA: 0s - loss: 5.6199e-05 - mean_absolute_error: 0.0063 22/126 [====>.........................] - ETA: 0s - loss: 1.0585e-04 - mean_absolute_error: 0.0079 40/126 [========>.....................] - ETA: 0s - loss: 1.0682e-04 - mean_absolute_error: 0.0080 56/126 [============>.................] - ETA: 0s - loss: 1.0765e-04 - mean_absolute_error: 0.0079 74/126 [================>.............] - ETA: 0s - loss: 1.0887e-04 - mean_absolute_error: 0.0080 92/126 [====================>.........] - ETA: 0s - loss: 1.0653e-04 - mean_absolute_error: 0.0079112/126 [=========================>....] - ETA: 0s - loss: 1.0687e-04 - mean_absolute_error: 0.0078126/126 [==============================] - 0s 3ms/step - loss: 1.0535e-04 - mean_absolute_error: 0.0078 - val_loss: 1.4180e-04 - val_mean_absolute_error: 0.0096
Epoch 23/100
1/126 [..............................] - ETA: 0s - loss: 8.2279e-05 - mean_absolute_error: 0.0069 22/126 [====>.........................] - ETA: 0s - loss: 1.0296e-04 - mean_absolute_error: 0.0078 43/126 [=========>....................] - ETA: 0s - loss: 1.1326e-04 - mean_absolute_error: 0.0080 64/126 [==============>...............] - ETA: 0s - loss: 1.1373e-04 - mean_absolute_error: 0.0081 85/126 [===================>..........] - ETA: 0s - loss: 1.1087e-04 - mean_absolute_error: 0.0080105/126 [========================>.....] - ETA: 0s - loss: 1.1056e-04 - mean_absolute_error: 0.0080125/126 [============================>.] - ETA: 0s - loss: 1.1003e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.1017e-04 - mean_absolute_error: 0.0080 - val_loss: 1.1931e-04 - val_mean_absolute_error: 0.0085
Epoch 24/100
1/126 [..............................] - ETA: 0s - loss: 1.3671e-04 - mean_absolute_error: 0.0091 22/126 [====>.........................] - ETA: 0s - loss: 1.1685e-04 - mean_absolute_error: 0.0079 43/126 [=========>....................] - ETA: 0s - loss: 1.1184e-04 - mean_absolute_error: 0.0079 63/126 [==============>...............] - ETA: 0s - loss: 1.0899e-04 - mean_absolute_error: 0.0078 83/126 [==================>...........] - ETA: 0s - loss: 1.0631e-04 - mean_absolute_error: 0.0078103/126 [=======================>......] - ETA: 0s - loss: 1.0541e-04 - mean_absolute_error: 0.0078124/126 [============================>.] - ETA: 0s - loss: 1.0664e-04 - mean_absolute_error: 0.0078126/126 [==============================] - 0s 3ms/step - loss: 1.0690e-04 - mean_absolute_error: 0.0078 - val_loss: 1.6401e-04 - val_mean_absolute_error: 0.0102
Epoch 25/100
1/126 [..............................] - ETA: 0s - loss: 1.4853e-04 - mean_absolute_error: 0.0103 22/126 [====>.........................] - ETA: 0s - loss: 1.4646e-04 - mean_absolute_error: 0.0094 43/126 [=========>....................] - ETA: 0s - loss: 1.2644e-04 - mean_absolute_error: 0.0087 64/126 [==============>...............] - ETA: 0s - loss: 1.2659e-04 - mean_absolute_error: 0.0086 85/126 [===================>..........] - ETA: 0s - loss: 1.2347e-04 - mean_absolute_error: 0.0085106/126 [========================>.....] - ETA: 0s - loss: 1.1836e-04 - mean_absolute_error: 0.0083126/126 [==============================] - ETA: 0s - loss: 1.1728e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 0s 3ms/step - loss: 1.1728e-04 - mean_absolute_error: 0.0082 - val_loss: 1.1328e-04 - val_mean_absolute_error: 0.0083
Epoch 26/100
1/126 [..............................] - ETA: 0s - loss: 9.3131e-05 - mean_absolute_error: 0.0073 22/126 [====>.........................] - ETA: 0s - loss: 1.0350e-04 - mean_absolute_error: 0.0077 43/126 [=========>....................] - ETA: 0s - loss: 1.0591e-04 - mean_absolute_error: 0.0076 64/126 [==============>...............] - ETA: 0s - loss: 1.0454e-04 - mean_absolute_error: 0.0076 85/126 [===================>..........] - ETA: 0s - loss: 1.0254e-04 - mean_absolute_error: 0.0076106/126 [========================>.....] - ETA: 0s - loss: 1.0161e-04 - mean_absolute_error: 0.0076126/126 [==============================] - ETA: 0s - loss: 1.0278e-04 - mean_absolute_error: 0.0076126/126 [==============================] - 0s 3ms/step - loss: 1.0278e-04 - mean_absolute_error: 0.0076 - val_loss: 1.3323e-04 - val_mean_absolute_error: 0.0092
Epoch 27/100
1/126 [..............................] - ETA: 0s - loss: 8.0296e-05 - mean_absolute_error: 0.0075 22/126 [====>.........................] - ETA: 0s - loss: 9.3678e-05 - mean_absolute_error: 0.0073 43/126 [=========>....................] - ETA: 0s - loss: 9.1663e-05 - mean_absolute_error: 0.0074 64/126 [==============>...............] - ETA: 0s - loss: 9.7508e-05 - mean_absolute_error: 0.0076 85/126 [===================>..........] - ETA: 0s - loss: 1.0505e-04 - mean_absolute_error: 0.0078106/126 [========================>.....] - ETA: 0s - loss: 1.1360e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1658e-04 - mean_absolute_error: 0.0082 - val_loss: 1.1225e-04 - val_mean_absolute_error: 0.0082
Epoch 28/100
1/126 [..............................] - ETA: 0s - loss: 9.0791e-05 - mean_absolute_error: 0.0078 22/126 [====>.........................] - ETA: 0s - loss: 1.1289e-04 - mean_absolute_error: 0.0081 42/126 [=========>....................] - ETA: 0s - loss: 1.1246e-04 - mean_absolute_error: 0.0081 62/126 [=============>................] - ETA: 0s - loss: 1.0827e-04 - mean_absolute_error: 0.0080 83/126 [==================>...........] - ETA: 0s - loss: 1.0379e-04 - mean_absolute_error: 0.0078104/126 [=======================>......] - ETA: 0s - loss: 1.0147e-04 - mean_absolute_error: 0.0077125/126 [============================>.] - ETA: 0s - loss: 1.0786e-04 - mean_absolute_error: 0.0079126/126 [==============================] - 0s 3ms/step - loss: 1.0762e-04 - mean_absolute_error: 0.0079 - val_loss: 1.1882e-04 - val_mean_absolute_error: 0.0085
Epoch 29/100
1/126 [..............................] - ETA: 0s - loss: 1.1556e-04 - mean_absolute_error: 0.0090 22/126 [====>.........................] - ETA: 0s - loss: 1.1360e-04 - mean_absolute_error: 0.0079 43/126 [=========>....................] - ETA: 0s - loss: 1.0414e-04 - mean_absolute_error: 0.0077 63/126 [==============>...............] - ETA: 0s - loss: 1.0649e-04 - mean_absolute_error: 0.0078 84/126 [===================>..........] - ETA: 0s - loss: 1.0807e-04 - mean_absolute_error: 0.0079104/126 [=======================>......] - ETA: 0s - loss: 1.0901e-04 - mean_absolute_error: 0.0079124/126 [============================>.] - ETA: 0s - loss: 1.0654e-04 - mean_absolute_error: 0.0078126/126 [==============================] - 0s 3ms/step - loss: 1.0689e-04 - mean_absolute_error: 0.0078 - val_loss: 1.2743e-04 - val_mean_absolute_error: 0.0090
Epoch 30/100
1/126 [..............................] - ETA: 0s - loss: 1.1184e-04 - mean_absolute_error: 0.0084 21/126 [====>.........................] - ETA: 0s - loss: 1.0368e-04 - mean_absolute_error: 0.0078 42/126 [=========>....................] - ETA: 0s - loss: 1.0332e-04 - mean_absolute_error: 0.0079 63/126 [==============>...............] - ETA: 0s - loss: 1.0602e-04 - mean_absolute_error: 0.0079 83/126 [==================>...........] - ETA: 0s - loss: 1.0383e-04 - mean_absolute_error: 0.0078104/126 [=======================>......] - ETA: 0s - loss: 1.0734e-04 - mean_absolute_error: 0.0079123/126 [============================>.] - ETA: 0s - loss: 1.0898e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.0874e-04 - mean_absolute_error: 0.0080 - val_loss: 1.1213e-04 - val_mean_absolute_error: 0.0083
Epoch 31/100
1/126 [..............................] - ETA: 0s - loss: 8.0893e-05 - mean_absolute_error: 0.0070 19/126 [===>..........................] - ETA: 0s - loss: 8.9110e-05 - mean_absolute_error: 0.0072 37/126 [=======>......................] - ETA: 0s - loss: 9.7465e-05 - mean_absolute_error: 0.0076 55/126 [============>.................] - ETA: 0s - loss: 1.0185e-04 - mean_absolute_error: 0.0078 73/126 [================>.............] - ETA: 0s - loss: 1.0558e-04 - mean_absolute_error: 0.0079 90/126 [====================>.........] - ETA: 0s - loss: 1.0659e-04 - mean_absolute_error: 0.0079107/126 [========================>.....] - ETA: 0s - loss: 1.0685e-04 - mean_absolute_error: 0.0079124/126 [============================>.] - ETA: 0s - loss: 1.0886e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.0876e-04 - mean_absolute_error: 0.0080 - val_loss: 1.3490e-04 - val_mean_absolute_error: 0.0093
Epoch 32/100
1/126 [..............................] - ETA: 0s - loss: 8.5625e-05 - mean_absolute_error: 0.0067 18/126 [===>..........................] - ETA: 0s - loss: 1.2516e-04 - mean_absolute_error: 0.0084 35/126 [=======>......................] - ETA: 0s - loss: 1.2551e-04 - mean_absolute_error: 0.0086 52/126 [===========>..................] - ETA: 0s - loss: 1.2433e-04 - mean_absolute_error: 0.0085 69/126 [===============>..............] - ETA: 0s - loss: 1.3251e-04 - mean_absolute_error: 0.0089 86/126 [===================>..........] - ETA: 0s - loss: 1.2915e-04 - mean_absolute_error: 0.0088102/126 [=======================>......] - ETA: 0s - loss: 1.3044e-04 - mean_absolute_error: 0.0088119/126 [===========================>..] - ETA: 0s - loss: 1.2591e-04 - mean_absolute_error: 0.0086126/126 [==============================] - 0s 3ms/step - loss: 1.2655e-04 - mean_absolute_error: 0.0086 - val_loss: 2.2375e-04 - val_mean_absolute_error: 0.0125
Epoch 33/100
1/126 [..............................] - ETA: 0s - loss: 2.1302e-04 - mean_absolute_error: 0.0116 18/126 [===>..........................] - ETA: 0s - loss: 1.6982e-04 - mean_absolute_error: 0.0104 36/126 [=======>......................] - ETA: 0s - loss: 1.8666e-04 - mean_absolute_error: 0.0109 53/126 [===========>..................] - ETA: 0s - loss: 1.7173e-04 - mean_absolute_error: 0.0104 70/126 [===============>..............] - ETA: 0s - loss: 1.7022e-04 - mean_absolute_error: 0.0103 88/126 [===================>..........] - ETA: 0s - loss: 1.6451e-04 - mean_absolute_error: 0.0101106/126 [========================>.....] - ETA: 0s - loss: 1.5788e-04 - mean_absolute_error: 0.0098124/126 [============================>.] - ETA: 0s - loss: 1.4947e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.4991e-04 - mean_absolute_error: 0.0095 - val_loss: 1.1306e-04 - val_mean_absolute_error: 0.0082
Epoch 34/100
1/126 [..............................] - ETA: 0s - loss: 1.2021e-04 - mean_absolute_error: 0.0084 18/126 [===>..........................] - ETA: 0s - loss: 1.0605e-04 - mean_absolute_error: 0.0078 35/126 [=======>......................] - ETA: 0s - loss: 1.0731e-04 - mean_absolute_error: 0.0078 53/126 [===========>..................] - ETA: 0s - loss: 1.1083e-04 - mean_absolute_error: 0.0079 70/126 [===============>..............] - ETA: 0s - loss: 1.1671e-04 - mean_absolute_error: 0.0082 86/126 [===================>..........] - ETA: 0s - loss: 1.1383e-04 - mean_absolute_error: 0.0082103/126 [=======================>......] - ETA: 0s - loss: 1.1379e-04 - mean_absolute_error: 0.0081121/126 [===========================>..] - ETA: 0s - loss: 1.1444e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 0s 3ms/step - loss: 1.1419e-04 - mean_absolute_error: 0.0082 - val_loss: 1.1487e-04 - val_mean_absolute_error: 0.0084
Epoch 35/100
1/126 [..............................] - ETA: 0s - loss: 1.9222e-04 - mean_absolute_error: 0.0083 20/126 [===>..........................] - ETA: 0s - loss: 1.0728e-04 - mean_absolute_error: 0.0078 38/126 [========>.....................] - ETA: 0s - loss: 1.1402e-04 - mean_absolute_error: 0.0080 56/126 [============>.................] - ETA: 0s - loss: 1.1643e-04 - mean_absolute_error: 0.0082 74/126 [================>.............] - ETA: 0s - loss: 1.1337e-04 - mean_absolute_error: 0.0082 92/126 [====================>.........] - ETA: 0s - loss: 1.1281e-04 - mean_absolute_error: 0.0081109/126 [========================>.....] - ETA: 0s - loss: 1.1181e-04 - mean_absolute_error: 0.0080126/126 [==============================] - ETA: 0s - loss: 1.1186e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1186e-04 - mean_absolute_error: 0.0081 - val_loss: 1.6039e-04 - val_mean_absolute_error: 0.0102
Epoch 36/100
1/126 [..............................] - ETA: 0s - loss: 1.5080e-04 - mean_absolute_error: 0.0083 18/126 [===>..........................] - ETA: 0s - loss: 1.1002e-04 - mean_absolute_error: 0.0080 36/126 [=======>......................] - ETA: 0s - loss: 1.0684e-04 - mean_absolute_error: 0.0078 54/126 [===========>..................] - ETA: 0s - loss: 1.1010e-04 - mean_absolute_error: 0.0079 72/126 [================>.............] - ETA: 0s - loss: 1.0778e-04 - mean_absolute_error: 0.0078 89/126 [====================>.........] - ETA: 0s - loss: 1.0900e-04 - mean_absolute_error: 0.0079107/126 [========================>.....] - ETA: 0s - loss: 1.1637e-04 - mean_absolute_error: 0.0082125/126 [============================>.] - ETA: 0s - loss: 1.1664e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 0s 3ms/step - loss: 1.1666e-04 - mean_absolute_error: 0.0082 - val_loss: 1.1682e-04 - val_mean_absolute_error: 0.0084
Epoch 37/100
1/126 [..............................] - ETA: 0s - loss: 8.2126e-05 - mean_absolute_error: 0.0076 17/126 [===>..........................] - ETA: 0s - loss: 1.0282e-04 - mean_absolute_error: 0.0075 32/126 [======>.......................] - ETA: 0s - loss: 1.0172e-04 - mean_absolute_error: 0.0077 50/126 [==========>...................] - ETA: 0s - loss: 1.2904e-04 - mean_absolute_error: 0.0086 67/126 [==============>...............] - ETA: 0s - loss: 1.2948e-04 - mean_absolute_error: 0.0087 83/126 [==================>...........] - ETA: 0s - loss: 1.2507e-04 - mean_absolute_error: 0.0085100/126 [======================>.......] - ETA: 0s - loss: 1.2097e-04 - mean_absolute_error: 0.0084117/126 [==========================>...] - ETA: 0s - loss: 1.1907e-04 - mean_absolute_error: 0.0083126/126 [==============================] - 0s 3ms/step - loss: 1.2006e-04 - mean_absolute_error: 0.0084 - val_loss: 1.3985e-04 - val_mean_absolute_error: 0.0095
Epoch 38/100
1/126 [..............................] - ETA: 0s - loss: 8.1872e-05 - mean_absolute_error: 0.0062 19/126 [===>..........................] - ETA: 0s - loss: 1.0998e-04 - mean_absolute_error: 0.0082 36/126 [=======>......................] - ETA: 0s - loss: 1.4112e-04 - mean_absolute_error: 0.0093 54/126 [===========>..................] - ETA: 0s - loss: 1.3595e-04 - mean_absolute_error: 0.0090 71/126 [===============>..............] - ETA: 0s - loss: 1.3128e-04 - mean_absolute_error: 0.0088 88/126 [===================>..........] - ETA: 0s - loss: 1.2777e-04 - mean_absolute_error: 0.0088105/126 [========================>.....] - ETA: 0s - loss: 1.2839e-04 - mean_absolute_error: 0.0088122/126 [============================>.] - ETA: 0s - loss: 1.2706e-04 - mean_absolute_error: 0.0087126/126 [==============================] - 0s 3ms/step - loss: 1.2644e-04 - mean_absolute_error: 0.0087 - val_loss: 1.0929e-04 - val_mean_absolute_error: 0.0080
Epoch 39/100
1/126 [..............................] - ETA: 0s - loss: 5.1663e-05 - mean_absolute_error: 0.0056 17/126 [===>..........................] - ETA: 0s - loss: 1.0133e-04 - mean_absolute_error: 0.0076 31/126 [======>.......................] - ETA: 0s - loss: 1.0539e-04 - mean_absolute_error: 0.0076 43/126 [=========>....................] - ETA: 0s - loss: 1.1540e-04 - mean_absolute_error: 0.0081 57/126 [============>.................] - ETA: 0s - loss: 1.2569e-04 - mean_absolute_error: 0.0085 71/126 [===============>..............] - ETA: 0s - loss: 1.2197e-04 - mean_absolute_error: 0.0085 85/126 [===================>..........] - ETA: 0s - loss: 1.1988e-04 - mean_absolute_error: 0.0083 99/126 [======================>.......] - ETA: 0s - loss: 1.1896e-04 - mean_absolute_error: 0.0083109/126 [========================>.....] - ETA: 0s - loss: 1.1671e-04 - mean_absolute_error: 0.0083124/126 [============================>.] - ETA: 0s - loss: 1.1495e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 1s 4ms/step - loss: 1.1526e-04 - mean_absolute_error: 0.0082 - val_loss: 2.1029e-04 - val_mean_absolute_error: 0.0118
Epoch 40/100
1/126 [..............................] - ETA: 0s - loss: 2.7374e-04 - mean_absolute_error: 0.0144 19/126 [===>..........................] - ETA: 0s - loss: 1.2252e-04 - mean_absolute_error: 0.0083 37/126 [=======>......................] - ETA: 0s - loss: 1.3166e-04 - mean_absolute_error: 0.0087 55/126 [============>.................] - ETA: 0s - loss: 1.2941e-04 - mean_absolute_error: 0.0087 73/126 [================>.............] - ETA: 0s - loss: 1.2091e-04 - mean_absolute_error: 0.0084 91/126 [====================>.........] - ETA: 0s - loss: 1.1817e-04 - mean_absolute_error: 0.0083109/126 [========================>.....] - ETA: 0s - loss: 1.2202e-04 - mean_absolute_error: 0.0085126/126 [==============================] - 0s 3ms/step - loss: 1.2364e-04 - mean_absolute_error: 0.0086 - val_loss: 3.2485e-04 - val_mean_absolute_error: 0.0154
Epoch 41/100
1/126 [..............................] - ETA: 0s - loss: 3.3520e-04 - mean_absolute_error: 0.0164 15/126 [==>...........................] - ETA: 0s - loss: 1.7361e-04 - mean_absolute_error: 0.0105 29/126 [=====>........................] - ETA: 0s - loss: 1.5473e-04 - mean_absolute_error: 0.0098 42/126 [=========>....................] - ETA: 0s - loss: 1.3794e-04 - mean_absolute_error: 0.0092 57/126 [============>.................] - ETA: 0s - loss: 1.3791e-04 - mean_absolute_error: 0.0092 75/126 [================>.............] - ETA: 0s - loss: 1.2993e-04 - mean_absolute_error: 0.0089 94/126 [=====================>........] - ETA: 0s - loss: 1.3008e-04 - mean_absolute_error: 0.0089113/126 [=========================>....] - ETA: 0s - loss: 1.2977e-04 - mean_absolute_error: 0.0088126/126 [==============================] - 0s 4ms/step - loss: 1.2845e-04 - mean_absolute_error: 0.0088 - val_loss: 2.5456e-04 - val_mean_absolute_error: 0.0135
Epoch 42/100
1/126 [..............................] - ETA: 0s - loss: 1.3564e-04 - mean_absolute_error: 0.0090 21/126 [====>.........................] - ETA: 0s - loss: 1.3599e-04 - mean_absolute_error: 0.0089 41/126 [========>.....................] - ETA: 0s - loss: 1.2434e-04 - mean_absolute_error: 0.0084 61/126 [=============>................] - ETA: 0s - loss: 1.1465e-04 - mean_absolute_error: 0.0081 81/126 [==================>...........] - ETA: 0s - loss: 1.1328e-04 - mean_absolute_error: 0.0081102/126 [=======================>......] - ETA: 0s - loss: 1.1279e-04 - mean_absolute_error: 0.0081123/126 [============================>.] - ETA: 0s - loss: 1.1101e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.1200e-04 - mean_absolute_error: 0.0081 - val_loss: 2.7870e-04 - val_mean_absolute_error: 0.0142
Epoch 43/100
1/126 [..............................] - ETA: 0s - loss: 2.0921e-04 - mean_absolute_error: 0.0126 22/126 [====>.........................] - ETA: 0s - loss: 2.1310e-04 - mean_absolute_error: 0.0117 43/126 [=========>....................] - ETA: 0s - loss: 1.7381e-04 - mean_absolute_error: 0.0104 64/126 [==============>...............] - ETA: 0s - loss: 1.5673e-04 - mean_absolute_error: 0.0097 85/126 [===================>..........] - ETA: 0s - loss: 1.4289e-04 - mean_absolute_error: 0.0092106/126 [========================>.....] - ETA: 0s - loss: 1.3653e-04 - mean_absolute_error: 0.0089126/126 [==============================] - ETA: 0s - loss: 1.3251e-04 - mean_absolute_error: 0.0088126/126 [==============================] - 0s 3ms/step - loss: 1.3251e-04 - mean_absolute_error: 0.0088 - val_loss: 1.2931e-04 - val_mean_absolute_error: 0.0091
Epoch 44/100
1/126 [..............................] - ETA: 0s - loss: 1.1536e-04 - mean_absolute_error: 0.0074 22/126 [====>.........................] - ETA: 0s - loss: 1.0934e-04 - mean_absolute_error: 0.0079 42/126 [=========>....................] - ETA: 0s - loss: 1.1828e-04 - mean_absolute_error: 0.0083 62/126 [=============>................] - ETA: 0s - loss: 1.1860e-04 - mean_absolute_error: 0.0083 83/126 [==================>...........] - ETA: 0s - loss: 1.0999e-04 - mean_absolute_error: 0.0080103/126 [=======================>......] - ETA: 0s - loss: 1.1253e-04 - mean_absolute_error: 0.0080124/126 [============================>.] - ETA: 0s - loss: 1.1406e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1409e-04 - mean_absolute_error: 0.0081 - val_loss: 1.8539e-04 - val_mean_absolute_error: 0.0112
Epoch 45/100
1/126 [..............................] - ETA: 0s - loss: 1.5585e-04 - mean_absolute_error: 0.0094 22/126 [====>.........................] - ETA: 0s - loss: 1.2366e-04 - mean_absolute_error: 0.0086 43/126 [=========>....................] - ETA: 0s - loss: 1.1508e-04 - mean_absolute_error: 0.0080 64/126 [==============>...............] - ETA: 0s - loss: 1.1135e-04 - mean_absolute_error: 0.0079 85/126 [===================>..........] - ETA: 0s - loss: 1.0982e-04 - mean_absolute_error: 0.0079106/126 [========================>.....] - ETA: 0s - loss: 1.0844e-04 - mean_absolute_error: 0.0079126/126 [==============================] - 0s 3ms/step - loss: 1.0857e-04 - mean_absolute_error: 0.0079 - val_loss: 1.1229e-04 - val_mean_absolute_error: 0.0082
Epoch 46/100
1/126 [..............................] - ETA: 0s - loss: 7.4692e-05 - mean_absolute_error: 0.0070 21/126 [====>.........................] - ETA: 0s - loss: 1.3659e-04 - mean_absolute_error: 0.0090 42/126 [=========>....................] - ETA: 0s - loss: 1.2349e-04 - mean_absolute_error: 0.0086 63/126 [==============>...............] - ETA: 0s - loss: 1.1461e-04 - mean_absolute_error: 0.0083 84/126 [===================>..........] - ETA: 0s - loss: 1.1469e-04 - mean_absolute_error: 0.0082105/126 [========================>.....] - ETA: 0s - loss: 1.1771e-04 - mean_absolute_error: 0.0083126/126 [==============================] - ETA: 0s - loss: 1.2628e-04 - mean_absolute_error: 0.0087126/126 [==============================] - 0s 3ms/step - loss: 1.2628e-04 - mean_absolute_error: 0.0087 - val_loss: 1.1828e-04 - val_mean_absolute_error: 0.0086
Epoch 47/100
1/126 [..............................] - ETA: 0s - loss: 8.0236e-05 - mean_absolute_error: 0.0073 22/126 [====>.........................] - ETA: 0s - loss: 1.0032e-04 - mean_absolute_error: 0.0078 43/126 [=========>....................] - ETA: 0s - loss: 1.0539e-04 - mean_absolute_error: 0.0079 65/126 [==============>...............] - ETA: 0s - loss: 1.0791e-04 - mean_absolute_error: 0.0079 86/126 [===================>..........] - ETA: 0s - loss: 1.0655e-04 - mean_absolute_error: 0.0080106/126 [========================>.....] - ETA: 0s - loss: 1.0888e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.1424e-04 - mean_absolute_error: 0.0082 - val_loss: 1.8934e-04 - val_mean_absolute_error: 0.0111
Epoch 48/100
1/126 [..............................] - ETA: 0s - loss: 1.7084e-04 - mean_absolute_error: 0.0114 22/126 [====>.........................] - ETA: 0s - loss: 1.4178e-04 - mean_absolute_error: 0.0094 42/126 [=========>....................] - ETA: 0s - loss: 1.3528e-04 - mean_absolute_error: 0.0090 63/126 [==============>...............] - ETA: 0s - loss: 1.2684e-04 - mean_absolute_error: 0.0087 84/126 [===================>..........] - ETA: 0s - loss: 1.2071e-04 - mean_absolute_error: 0.0084105/126 [========================>.....] - ETA: 0s - loss: 1.1664e-04 - mean_absolute_error: 0.0083125/126 [============================>.] - ETA: 0s - loss: 1.1301e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1291e-04 - mean_absolute_error: 0.0081 - val_loss: 1.2274e-04 - val_mean_absolute_error: 0.0087
Epoch 49/100
1/126 [..............................] - ETA: 0s - loss: 6.4768e-05 - mean_absolute_error: 0.0068 22/126 [====>.........................] - ETA: 0s - loss: 1.1285e-04 - mean_absolute_error: 0.0083 43/126 [=========>....................] - ETA: 0s - loss: 1.1443e-04 - mean_absolute_error: 0.0082 64/126 [==============>...............] - ETA: 0s - loss: 1.1094e-04 - mean_absolute_error: 0.0081 85/126 [===================>..........] - ETA: 0s - loss: 1.0896e-04 - mean_absolute_error: 0.0081106/126 [========================>.....] - ETA: 0s - loss: 1.0951e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.1096e-04 - mean_absolute_error: 0.0081 - val_loss: 1.3554e-04 - val_mean_absolute_error: 0.0092
Epoch 50/100
1/126 [..............................] - ETA: 0s - loss: 1.4362e-04 - mean_absolute_error: 0.0100 21/126 [====>.........................] - ETA: 0s - loss: 1.1825e-04 - mean_absolute_error: 0.0084 42/126 [=========>....................] - ETA: 0s - loss: 1.1122e-04 - mean_absolute_error: 0.0082 63/126 [==============>...............] - ETA: 0s - loss: 1.0832e-04 - mean_absolute_error: 0.0080 81/126 [==================>...........] - ETA: 0s - loss: 1.1227e-04 - mean_absolute_error: 0.0081 99/126 [======================>.......] - ETA: 0s - loss: 1.1435e-04 - mean_absolute_error: 0.0082117/126 [==========================>...] - ETA: 0s - loss: 1.1255e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1786e-04 - mean_absolute_error: 0.0083 - val_loss: 2.0597e-04 - val_mean_absolute_error: 0.0119
Epoch 51/100
1/126 [..............................] - ETA: 0s - loss: 1.5007e-04 - mean_absolute_error: 0.0095 19/126 [===>..........................] - ETA: 0s - loss: 1.6572e-04 - mean_absolute_error: 0.0101 37/126 [=======>......................] - ETA: 0s - loss: 1.5097e-04 - mean_absolute_error: 0.0096 54/126 [===========>..................] - ETA: 0s - loss: 1.5160e-04 - mean_absolute_error: 0.0095 72/126 [================>.............] - ETA: 0s - loss: 1.4699e-04 - mean_absolute_error: 0.0094 89/126 [====================>.........] - ETA: 0s - loss: 1.3708e-04 - mean_absolute_error: 0.0091105/126 [========================>.....] - ETA: 0s - loss: 1.3094e-04 - mean_absolute_error: 0.0088122/126 [============================>.] - ETA: 0s - loss: 1.2670e-04 - mean_absolute_error: 0.0087126/126 [==============================] - 0s 3ms/step - loss: 1.2610e-04 - mean_absolute_error: 0.0087 - val_loss: 1.0663e-04 - val_mean_absolute_error: 0.0080
Epoch 52/100
1/126 [..............................] - ETA: 0s - loss: 8.8847e-05 - mean_absolute_error: 0.0073 20/126 [===>..........................] - ETA: 0s - loss: 1.6200e-04 - mean_absolute_error: 0.0101 39/126 [========>.....................] - ETA: 0s - loss: 1.5971e-04 - mean_absolute_error: 0.0099 57/126 [============>.................] - ETA: 0s - loss: 1.3909e-04 - mean_absolute_error: 0.0091 76/126 [=================>............] - ETA: 0s - loss: 1.3701e-04 - mean_absolute_error: 0.0091 96/126 [=====================>........] - ETA: 0s - loss: 1.3870e-04 - mean_absolute_error: 0.0091116/126 [==========================>...] - ETA: 0s - loss: 1.3738e-04 - mean_absolute_error: 0.0091126/126 [==============================] - 0s 3ms/step - loss: 1.3455e-04 - mean_absolute_error: 0.0090 - val_loss: 1.1103e-04 - val_mean_absolute_error: 0.0083
Epoch 53/100
1/126 [..............................] - ETA: 0s - loss: 4.0859e-05 - mean_absolute_error: 0.0049 21/126 [====>.........................] - ETA: 0s - loss: 1.2128e-04 - mean_absolute_error: 0.0083 42/126 [=========>....................] - ETA: 0s - loss: 1.0889e-04 - mean_absolute_error: 0.0079 63/126 [==============>...............] - ETA: 0s - loss: 1.0892e-04 - mean_absolute_error: 0.0079 83/126 [==================>...........] - ETA: 0s - loss: 1.0802e-04 - mean_absolute_error: 0.0080104/126 [=======================>......] - ETA: 0s - loss: 1.1301e-04 - mean_absolute_error: 0.0082124/126 [============================>.] - ETA: 0s - loss: 1.1277e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 0s 3ms/step - loss: 1.1281e-04 - mean_absolute_error: 0.0082 - val_loss: 3.1077e-04 - val_mean_absolute_error: 0.0150
Epoch 54/100
1/126 [..............................] - ETA: 0s - loss: 2.6683e-04 - mean_absolute_error: 0.0141 22/126 [====>.........................] - ETA: 0s - loss: 2.0834e-04 - mean_absolute_error: 0.0117 43/126 [=========>....................] - ETA: 0s - loss: 1.8356e-04 - mean_absolute_error: 0.0107 64/126 [==============>...............] - ETA: 0s - loss: 1.6739e-04 - mean_absolute_error: 0.0101 85/126 [===================>..........] - ETA: 0s - loss: 1.5335e-04 - mean_absolute_error: 0.0096106/126 [========================>.....] - ETA: 0s - loss: 1.4474e-04 - mean_absolute_error: 0.0093126/126 [==============================] - ETA: 0s - loss: 1.3612e-04 - mean_absolute_error: 0.0090126/126 [==============================] - 0s 3ms/step - loss: 1.3612e-04 - mean_absolute_error: 0.0090 - val_loss: 1.0688e-04 - val_mean_absolute_error: 0.0079
Epoch 55/100
1/126 [..............................] - ETA: 0s - loss: 9.7417e-05 - mean_absolute_error: 0.0088 22/126 [====>.........................] - ETA: 0s - loss: 1.0659e-04 - mean_absolute_error: 0.0081 42/126 [=========>....................] - ETA: 0s - loss: 1.0451e-04 - mean_absolute_error: 0.0079 63/126 [==============>...............] - ETA: 0s - loss: 1.0282e-04 - mean_absolute_error: 0.0077 84/126 [===================>..........] - ETA: 0s - loss: 1.0213e-04 - mean_absolute_error: 0.0077104/126 [=======================>......] - ETA: 0s - loss: 1.0348e-04 - mean_absolute_error: 0.0078124/126 [============================>.] - ETA: 0s - loss: 1.0493e-04 - mean_absolute_error: 0.0078126/126 [==============================] - 0s 3ms/step - loss: 1.0469e-04 - mean_absolute_error: 0.0078 - val_loss: 1.2286e-04 - val_mean_absolute_error: 0.0087
Epoch 56/100
1/126 [..............................] - ETA: 0s - loss: 1.4507e-04 - mean_absolute_error: 0.0094 21/126 [====>.........................] - ETA: 0s - loss: 1.0358e-04 - mean_absolute_error: 0.0079 42/126 [=========>....................] - ETA: 0s - loss: 1.0505e-04 - mean_absolute_error: 0.0079 63/126 [==============>...............] - ETA: 0s - loss: 1.0165e-04 - mean_absolute_error: 0.0077 84/126 [===================>..........] - ETA: 0s - loss: 1.0132e-04 - mean_absolute_error: 0.0078104/126 [=======================>......] - ETA: 0s - loss: 1.0078e-04 - mean_absolute_error: 0.0078125/126 [============================>.] - ETA: 0s - loss: 1.0749e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.0772e-04 - mean_absolute_error: 0.0080 - val_loss: 1.2665e-04 - val_mean_absolute_error: 0.0088
Epoch 57/100
1/126 [..............................] - ETA: 0s - loss: 1.1632e-04 - mean_absolute_error: 0.0085 22/126 [====>.........................] - ETA: 0s - loss: 1.3683e-04 - mean_absolute_error: 0.0090 43/126 [=========>....................] - ETA: 0s - loss: 1.3615e-04 - mean_absolute_error: 0.0090 64/126 [==============>...............] - ETA: 0s - loss: 1.4533e-04 - mean_absolute_error: 0.0094 85/126 [===================>..........] - ETA: 0s - loss: 1.4376e-04 - mean_absolute_error: 0.0093106/126 [========================>.....] - ETA: 0s - loss: 1.3579e-04 - mean_absolute_error: 0.0090126/126 [==============================] - 0s 3ms/step - loss: 1.2880e-04 - mean_absolute_error: 0.0087 - val_loss: 1.8014e-04 - val_mean_absolute_error: 0.0108
Epoch 58/100
1/126 [..............................] - ETA: 0s - loss: 1.1429e-04 - mean_absolute_error: 0.0087 22/126 [====>.........................] - ETA: 0s - loss: 1.0666e-04 - mean_absolute_error: 0.0080 43/126 [=========>....................] - ETA: 0s - loss: 1.0483e-04 - mean_absolute_error: 0.0077 64/126 [==============>...............] - ETA: 0s - loss: 9.8561e-05 - mean_absolute_error: 0.0075 85/126 [===================>..........] - ETA: 0s - loss: 1.0596e-04 - mean_absolute_error: 0.0079106/126 [========================>.....] - ETA: 0s - loss: 1.1318e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 0s 3ms/step - loss: 1.1833e-04 - mean_absolute_error: 0.0083 - val_loss: 1.5130e-04 - val_mean_absolute_error: 0.0098
Epoch 59/100
1/126 [..............................] - ETA: 0s - loss: 8.8706e-05 - mean_absolute_error: 0.0081 22/126 [====>.........................] - ETA: 0s - loss: 1.2088e-04 - mean_absolute_error: 0.0087 43/126 [=========>....................] - ETA: 0s - loss: 1.2998e-04 - mean_absolute_error: 0.0089 64/126 [==============>...............] - ETA: 0s - loss: 1.2969e-04 - mean_absolute_error: 0.0089 85/126 [===================>..........] - ETA: 0s - loss: 1.2760e-04 - mean_absolute_error: 0.0088105/126 [========================>.....] - ETA: 0s - loss: 1.2299e-04 - mean_absolute_error: 0.0086125/126 [============================>.] - ETA: 0s - loss: 1.1959e-04 - mean_absolute_error: 0.0085126/126 [==============================] - 0s 3ms/step - loss: 1.1944e-04 - mean_absolute_error: 0.0085 - val_loss: 1.0728e-04 - val_mean_absolute_error: 0.0081
Epoch 60/100
1/126 [..............................] - ETA: 0s - loss: 1.3714e-04 - mean_absolute_error: 0.0076 22/126 [====>.........................] - ETA: 0s - loss: 1.0398e-04 - mean_absolute_error: 0.0077 43/126 [=========>....................] - ETA: 0s - loss: 1.3303e-04 - mean_absolute_error: 0.0090 64/126 [==============>...............] - ETA: 0s - loss: 1.4510e-04 - mean_absolute_error: 0.0095 85/126 [===================>..........] - ETA: 0s - loss: 1.3226e-04 - mean_absolute_error: 0.0090106/126 [========================>.....] - ETA: 0s - loss: 1.2699e-04 - mean_absolute_error: 0.0087126/126 [==============================] - ETA: 0s - loss: 1.2270e-04 - mean_absolute_error: 0.0085126/126 [==============================] - 0s 3ms/step - loss: 1.2270e-04 - mean_absolute_error: 0.0085 - val_loss: 1.5810e-04 - val_mean_absolute_error: 0.0102
Epoch 61/100
1/126 [..............................] - ETA: 0s - loss: 1.2113e-04 - mean_absolute_error: 0.0086 22/126 [====>.........................] - ETA: 0s - loss: 1.3133e-04 - mean_absolute_error: 0.0089 43/126 [=========>....................] - ETA: 0s - loss: 1.2993e-04 - mean_absolute_error: 0.0089 64/126 [==============>...............] - ETA: 0s - loss: 1.2687e-04 - mean_absolute_error: 0.0087 85/126 [===================>..........] - ETA: 0s - loss: 1.2186e-04 - mean_absolute_error: 0.0085106/126 [========================>.....] - ETA: 0s - loss: 1.1546e-04 - mean_absolute_error: 0.0083126/126 [==============================] - 0s 3ms/step - loss: 1.1613e-04 - mean_absolute_error: 0.0083 - val_loss: 1.9923e-04 - val_mean_absolute_error: 0.0117
Epoch 62/100
1/126 [..............................] - ETA: 0s - loss: 1.1420e-04 - mean_absolute_error: 0.0090 22/126 [====>.........................] - ETA: 0s - loss: 1.4724e-04 - mean_absolute_error: 0.0092 43/126 [=========>....................] - ETA: 0s - loss: 1.2731e-04 - mean_absolute_error: 0.0085 64/126 [==============>...............] - ETA: 0s - loss: 1.1785e-04 - mean_absolute_error: 0.0083 85/126 [===================>..........] - ETA: 0s - loss: 1.1052e-04 - mean_absolute_error: 0.0080106/126 [========================>.....] - ETA: 0s - loss: 1.1074e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.1215e-04 - mean_absolute_error: 0.0081 - val_loss: 1.9087e-04 - val_mean_absolute_error: 0.0112
Epoch 63/100
1/126 [..............................] - ETA: 0s - loss: 2.0599e-04 - mean_absolute_error: 0.0122 22/126 [====>.........................] - ETA: 0s - loss: 1.4263e-04 - mean_absolute_error: 0.0094 43/126 [=========>....................] - ETA: 0s - loss: 1.2888e-04 - mean_absolute_error: 0.0088 64/126 [==============>...............] - ETA: 0s - loss: 1.2981e-04 - mean_absolute_error: 0.0088 84/126 [===================>..........] - ETA: 0s - loss: 1.2517e-04 - mean_absolute_error: 0.0087105/126 [========================>.....] - ETA: 0s - loss: 1.4218e-04 - mean_absolute_error: 0.0093126/126 [==============================] - ETA: 0s - loss: 1.3790e-04 - mean_absolute_error: 0.0091126/126 [==============================] - 0s 3ms/step - loss: 1.3790e-04 - mean_absolute_error: 0.0091 - val_loss: 1.2231e-04 - val_mean_absolute_error: 0.0088
Epoch 64/100
1/126 [..............................] - ETA: 0s - loss: 6.5547e-05 - mean_absolute_error: 0.0063 22/126 [====>.........................] - ETA: 0s - loss: 8.3831e-05 - mean_absolute_error: 0.0071 43/126 [=========>....................] - ETA: 0s - loss: 9.2433e-05 - mean_absolute_error: 0.0074 64/126 [==============>...............] - ETA: 0s - loss: 1.0204e-04 - mean_absolute_error: 0.0077 85/126 [===================>..........] - ETA: 0s - loss: 1.1071e-04 - mean_absolute_error: 0.0081106/126 [========================>.....] - ETA: 0s - loss: 1.0897e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.1390e-04 - mean_absolute_error: 0.0082 - val_loss: 1.0688e-04 - val_mean_absolute_error: 0.0081
Epoch 65/100
1/126 [..............................] - ETA: 0s - loss: 6.3875e-05 - mean_absolute_error: 0.0061 22/126 [====>.........................] - ETA: 0s - loss: 1.1256e-04 - mean_absolute_error: 0.0077 43/126 [=========>....................] - ETA: 0s - loss: 9.7870e-05 - mean_absolute_error: 0.0073 64/126 [==============>...............] - ETA: 0s - loss: 9.5076e-05 - mean_absolute_error: 0.0073 85/126 [===================>..........] - ETA: 0s - loss: 9.7158e-05 - mean_absolute_error: 0.0073106/126 [========================>.....] - ETA: 0s - loss: 9.5586e-05 - mean_absolute_error: 0.0074126/126 [==============================] - ETA: 0s - loss: 9.9390e-05 - mean_absolute_error: 0.0075126/126 [==============================] - 0s 3ms/step - loss: 9.9390e-05 - mean_absolute_error: 0.0075 - val_loss: 1.1826e-04 - val_mean_absolute_error: 0.0085
Epoch 66/100
1/126 [..............................] - ETA: 0s - loss: 7.5968e-05 - mean_absolute_error: 0.0070 22/126 [====>.........................] - ETA: 0s - loss: 1.2372e-04 - mean_absolute_error: 0.0083 43/126 [=========>....................] - ETA: 0s - loss: 1.1053e-04 - mean_absolute_error: 0.0080 63/126 [==============>...............] - ETA: 0s - loss: 1.0609e-04 - mean_absolute_error: 0.0078 83/126 [==================>...........] - ETA: 0s - loss: 1.0292e-04 - mean_absolute_error: 0.0077104/126 [=======================>......] - ETA: 0s - loss: 1.1253e-04 - mean_absolute_error: 0.0080124/126 [============================>.] - ETA: 0s - loss: 1.1538e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 0s 3ms/step - loss: 1.1508e-04 - mean_absolute_error: 0.0082 - val_loss: 1.2063e-04 - val_mean_absolute_error: 0.0088
Epoch 67/100
1/126 [..............................] - ETA: 0s - loss: 9.6540e-05 - mean_absolute_error: 0.0080 22/126 [====>.........................] - ETA: 0s - loss: 9.4563e-05 - mean_absolute_error: 0.0072 43/126 [=========>....................] - ETA: 0s - loss: 9.8812e-05 - mean_absolute_error: 0.0075 64/126 [==============>...............] - ETA: 0s - loss: 1.0038e-04 - mean_absolute_error: 0.0076 85/126 [===================>..........] - ETA: 0s - loss: 9.8249e-05 - mean_absolute_error: 0.0075106/126 [========================>.....] - ETA: 0s - loss: 1.0310e-04 - mean_absolute_error: 0.0077126/126 [==============================] - 0s 3ms/step - loss: 1.1050e-04 - mean_absolute_error: 0.0080 - val_loss: 1.8694e-04 - val_mean_absolute_error: 0.0113
Epoch 68/100
1/126 [..............................] - ETA: 0s - loss: 1.4987e-04 - mean_absolute_error: 0.0096 22/126 [====>.........................] - ETA: 0s - loss: 1.4244e-04 - mean_absolute_error: 0.0091 43/126 [=========>....................] - ETA: 0s - loss: 1.2869e-04 - mean_absolute_error: 0.0088 64/126 [==============>...............] - ETA: 0s - loss: 1.2835e-04 - mean_absolute_error: 0.0088 85/126 [===================>..........] - ETA: 0s - loss: 1.2425e-04 - mean_absolute_error: 0.0086106/126 [========================>.....] - ETA: 0s - loss: 1.2299e-04 - mean_absolute_error: 0.0086126/126 [==============================] - ETA: 0s - loss: 1.2255e-04 - mean_absolute_error: 0.0086126/126 [==============================] - 0s 3ms/step - loss: 1.2255e-04 - mean_absolute_error: 0.0086 - val_loss: 1.1327e-04 - val_mean_absolute_error: 0.0084
Epoch 69/100
1/126 [..............................] - ETA: 0s - loss: 1.0408e-04 - mean_absolute_error: 0.0080 22/126 [====>.........................] - ETA: 0s - loss: 9.0359e-05 - mean_absolute_error: 0.0073 43/126 [=========>....................] - ETA: 0s - loss: 1.0109e-04 - mean_absolute_error: 0.0077 64/126 [==============>...............] - ETA: 0s - loss: 1.1084e-04 - mean_absolute_error: 0.0081 85/126 [===================>..........] - ETA: 0s - loss: 1.2402e-04 - mean_absolute_error: 0.0086106/126 [========================>.....] - ETA: 0s - loss: 1.1714e-04 - mean_absolute_error: 0.0083126/126 [==============================] - 0s 3ms/step - loss: 1.1493e-04 - mean_absolute_error: 0.0083 - val_loss: 1.1329e-04 - val_mean_absolute_error: 0.0084
Epoch 70/100
1/126 [..............................] - ETA: 0s - loss: 5.6848e-05 - mean_absolute_error: 0.0063 22/126 [====>.........................] - ETA: 0s - loss: 1.3746e-04 - mean_absolute_error: 0.0090 43/126 [=========>....................] - ETA: 0s - loss: 1.4225e-04 - mean_absolute_error: 0.0093 63/126 [==============>...............] - ETA: 0s - loss: 1.3274e-04 - mean_absolute_error: 0.0090 84/126 [===================>..........] - ETA: 0s - loss: 1.2842e-04 - mean_absolute_error: 0.0087104/126 [=======================>......] - ETA: 0s - loss: 1.1872e-04 - mean_absolute_error: 0.0084125/126 [============================>.] - ETA: 0s - loss: 1.2552e-04 - mean_absolute_error: 0.0086126/126 [==============================] - 0s 3ms/step - loss: 1.2584e-04 - mean_absolute_error: 0.0086 - val_loss: 1.1152e-04 - val_mean_absolute_error: 0.0083
Epoch 71/100
1/126 [..............................] - ETA: 0s - loss: 8.7693e-05 - mean_absolute_error: 0.0074 22/126 [====>.........................] - ETA: 0s - loss: 1.4397e-04 - mean_absolute_error: 0.0094 43/126 [=========>....................] - ETA: 0s - loss: 1.2978e-04 - mean_absolute_error: 0.0089 64/126 [==============>...............] - ETA: 0s - loss: 1.3200e-04 - mean_absolute_error: 0.0090 85/126 [===================>..........] - ETA: 0s - loss: 1.4150e-04 - mean_absolute_error: 0.0093106/126 [========================>.....] - ETA: 0s - loss: 1.4286e-04 - mean_absolute_error: 0.0093126/126 [==============================] - 0s 3ms/step - loss: 1.3806e-04 - mean_absolute_error: 0.0092 - val_loss: 1.1511e-04 - val_mean_absolute_error: 0.0085
Epoch 72/100
1/126 [..............................] - ETA: 0s - loss: 7.0298e-05 - mean_absolute_error: 0.0072 21/126 [====>.........................] - ETA: 0s - loss: 1.1721e-04 - mean_absolute_error: 0.0083 42/126 [=========>....................] - ETA: 0s - loss: 1.1498e-04 - mean_absolute_error: 0.0083 63/126 [==============>...............] - ETA: 0s - loss: 1.0889e-04 - mean_absolute_error: 0.0080 84/126 [===================>..........] - ETA: 0s - loss: 1.0845e-04 - mean_absolute_error: 0.0079105/126 [========================>.....] - ETA: 0s - loss: 1.1444e-04 - mean_absolute_error: 0.0082126/126 [==============================] - ETA: 0s - loss: 1.1545e-04 - mean_absolute_error: 0.0083126/126 [==============================] - 0s 3ms/step - loss: 1.1545e-04 - mean_absolute_error: 0.0083 - val_loss: 1.0302e-04 - val_mean_absolute_error: 0.0079
Epoch 73/100
1/126 [..............................] - ETA: 0s - loss: 2.1025e-04 - mean_absolute_error: 0.0080 22/126 [====>.........................] - ETA: 0s - loss: 1.0563e-04 - mean_absolute_error: 0.0078 43/126 [=========>....................] - ETA: 0s - loss: 1.0802e-04 - mean_absolute_error: 0.0079 64/126 [==============>...............] - ETA: 0s - loss: 1.0516e-04 - mean_absolute_error: 0.0078 82/126 [==================>...........] - ETA: 0s - loss: 1.0765e-04 - mean_absolute_error: 0.0079101/126 [=======================>......] - ETA: 0s - loss: 1.0994e-04 - mean_absolute_error: 0.0080119/126 [===========================>..] - ETA: 0s - loss: 1.0490e-04 - mean_absolute_error: 0.0078126/126 [==============================] - 0s 3ms/step - loss: 1.0493e-04 - mean_absolute_error: 0.0078 - val_loss: 1.1361e-04 - val_mean_absolute_error: 0.0083
Epoch 74/100
1/126 [..............................] - ETA: 0s - loss: 5.1408e-05 - mean_absolute_error: 0.0059 20/126 [===>..........................] - ETA: 0s - loss: 9.8494e-05 - mean_absolute_error: 0.0075 38/126 [========>.....................] - ETA: 0s - loss: 1.0252e-04 - mean_absolute_error: 0.0078 55/126 [============>.................] - ETA: 0s - loss: 9.6211e-05 - mean_absolute_error: 0.0076 73/126 [================>.............] - ETA: 0s - loss: 1.0236e-04 - mean_absolute_error: 0.0077 92/126 [====================>.........] - ETA: 0s - loss: 1.0363e-04 - mean_absolute_error: 0.0077111/126 [=========================>....] - ETA: 0s - loss: 1.0328e-04 - mean_absolute_error: 0.0077126/126 [==============================] - 0s 3ms/step - loss: 1.0148e-04 - mean_absolute_error: 0.0076 - val_loss: 1.1141e-04 - val_mean_absolute_error: 0.0083
Epoch 75/100
1/126 [..............................] - ETA: 0s - loss: 8.0596e-05 - mean_absolute_error: 0.0071 19/126 [===>..........................] - ETA: 0s - loss: 1.1330e-04 - mean_absolute_error: 0.0083 38/126 [========>.....................] - ETA: 0s - loss: 1.1695e-04 - mean_absolute_error: 0.0084 57/126 [============>.................] - ETA: 0s - loss: 1.0998e-04 - mean_absolute_error: 0.0081 75/126 [================>.............] - ETA: 0s - loss: 1.0718e-04 - mean_absolute_error: 0.0080 93/126 [=====================>........] - ETA: 0s - loss: 1.0668e-04 - mean_absolute_error: 0.0080111/126 [=========================>....] - ETA: 0s - loss: 1.0659e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.0433e-04 - mean_absolute_error: 0.0078 - val_loss: 2.2343e-04 - val_mean_absolute_error: 0.0123
Epoch 76/100
1/126 [..............................] - ETA: 0s - loss: 2.1239e-04 - mean_absolute_error: 0.0122 20/126 [===>..........................] - ETA: 0s - loss: 1.1469e-04 - mean_absolute_error: 0.0084 38/126 [========>.....................] - ETA: 0s - loss: 1.0998e-04 - mean_absolute_error: 0.0081 56/126 [============>.................] - ETA: 0s - loss: 1.0322e-04 - mean_absolute_error: 0.0078 73/126 [================>.............] - ETA: 0s - loss: 1.0275e-04 - mean_absolute_error: 0.0078 90/126 [====================>.........] - ETA: 0s - loss: 1.0886e-04 - mean_absolute_error: 0.0081108/126 [========================>.....] - ETA: 0s - loss: 1.1908e-04 - mean_absolute_error: 0.0084126/126 [==============================] - ETA: 0s - loss: 1.2539e-04 - mean_absolute_error: 0.0087126/126 [==============================] - 0s 3ms/step - loss: 1.2539e-04 - mean_absolute_error: 0.0087 - val_loss: 1.2020e-04 - val_mean_absolute_error: 0.0086
Epoch 77/100
1/126 [..............................] - ETA: 0s - loss: 3.2380e-04 - mean_absolute_error: 0.0109 19/126 [===>..........................] - ETA: 0s - loss: 1.3551e-04 - mean_absolute_error: 0.0086 35/126 [=======>......................] - ETA: 0s - loss: 1.2040e-04 - mean_absolute_error: 0.0083 52/126 [===========>..................] - ETA: 0s - loss: 1.1333e-04 - mean_absolute_error: 0.0081 70/126 [===============>..............] - ETA: 0s - loss: 1.1449e-04 - mean_absolute_error: 0.0082 87/126 [===================>..........] - ETA: 0s - loss: 1.0923e-04 - mean_absolute_error: 0.0080104/126 [=======================>......] - ETA: 0s - loss: 1.0536e-04 - mean_absolute_error: 0.0079121/126 [===========================>..] - ETA: 0s - loss: 1.0472e-04 - mean_absolute_error: 0.0078126/126 [==============================] - 0s 3ms/step - loss: 1.0407e-04 - mean_absolute_error: 0.0078 - val_loss: 1.0091e-04 - val_mean_absolute_error: 0.0077
Epoch 78/100
1/126 [..............................] - ETA: 0s - loss: 1.2548e-04 - mean_absolute_error: 0.0087 20/126 [===>..........................] - ETA: 0s - loss: 1.0914e-04 - mean_absolute_error: 0.0081 39/126 [========>.....................] - ETA: 0s - loss: 1.1157e-04 - mean_absolute_error: 0.0083 57/126 [============>.................] - ETA: 0s - loss: 1.1211e-04 - mean_absolute_error: 0.0082 74/126 [================>.............] - ETA: 0s - loss: 1.0809e-04 - mean_absolute_error: 0.0080 92/126 [====================>.........] - ETA: 0s - loss: 1.1392e-04 - mean_absolute_error: 0.0082110/126 [=========================>....] - ETA: 0s - loss: 1.1363e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 0s 3ms/step - loss: 1.1190e-04 - mean_absolute_error: 0.0081 - val_loss: 1.0609e-04 - val_mean_absolute_error: 0.0081
Epoch 79/100
1/126 [..............................] - ETA: 0s - loss: 4.7690e-05 - mean_absolute_error: 0.0056 18/126 [===>..........................] - ETA: 0s - loss: 9.3385e-05 - mean_absolute_error: 0.0076 36/126 [=======>......................] - ETA: 0s - loss: 1.1060e-04 - mean_absolute_error: 0.0081 53/126 [===========>..................] - ETA: 0s - loss: 1.1858e-04 - mean_absolute_error: 0.0085 71/126 [===============>..............] - ETA: 0s - loss: 1.1117e-04 - mean_absolute_error: 0.0082 88/126 [===================>..........] - ETA: 0s - loss: 1.0956e-04 - mean_absolute_error: 0.0081105/126 [========================>.....] - ETA: 0s - loss: 1.0875e-04 - mean_absolute_error: 0.0080122/126 [============================>.] - ETA: 0s - loss: 1.0952e-04 - mean_absolute_error: 0.0080126/126 [==============================] - 0s 3ms/step - loss: 1.1000e-04 - mean_absolute_error: 0.0080 - val_loss: 1.0613e-04 - val_mean_absolute_error: 0.0081
Epoch 80/100
1/126 [..............................] - ETA: 0s - loss: 1.3843e-04 - mean_absolute_error: 0.0088 20/126 [===>..........................] - ETA: 0s - loss: 1.0911e-04 - mean_absolute_error: 0.0080 38/126 [========>.....................] - ETA: 0s - loss: 1.1412e-04 - mean_absolute_error: 0.0081 56/126 [============>.................] - ETA: 0s - loss: 1.0516e-04 - mean_absolute_error: 0.0078 74/126 [================>.............] - ETA: 0s - loss: 1.0200e-04 - mean_absolute_error: 0.0077 91/126 [====================>.........] - ETA: 0s - loss: 1.0271e-04 - mean_absolute_error: 0.0077109/126 [========================>.....] - ETA: 0s - loss: 1.0050e-04 - mean_absolute_error: 0.0076126/126 [==============================] - ETA: 0s - loss: 1.0248e-04 - mean_absolute_error: 0.0077126/126 [==============================] - 0s 3ms/step - loss: 1.0248e-04 - mean_absolute_error: 0.0077 - val_loss: 1.7342e-04 - val_mean_absolute_error: 0.0106
Epoch 81/100
1/126 [..............................] - ETA: 0s - loss: 1.3025e-04 - mean_absolute_error: 0.0095 19/126 [===>..........................] - ETA: 0s - loss: 1.1131e-04 - mean_absolute_error: 0.0084 37/126 [=======>......................] - ETA: 0s - loss: 1.1926e-04 - mean_absolute_error: 0.0084 55/126 [============>.................] - ETA: 0s - loss: 1.1704e-04 - mean_absolute_error: 0.0082 73/126 [================>.............] - ETA: 0s - loss: 1.1137e-04 - mean_absolute_error: 0.0080 91/126 [====================>.........] - ETA: 0s - loss: 1.1404e-04 - mean_absolute_error: 0.0082108/126 [========================>.....] - ETA: 0s - loss: 1.1130e-04 - mean_absolute_error: 0.0081126/126 [==============================] - ETA: 0s - loss: 1.1165e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1165e-04 - mean_absolute_error: 0.0081 - val_loss: 1.4054e-04 - val_mean_absolute_error: 0.0095
Epoch 82/100
1/126 [..............................] - ETA: 0s - loss: 8.3696e-05 - mean_absolute_error: 0.0077 18/126 [===>..........................] - ETA: 0s - loss: 9.9873e-05 - mean_absolute_error: 0.0078 36/126 [=======>......................] - ETA: 0s - loss: 9.7865e-05 - mean_absolute_error: 0.0075 53/126 [===========>..................] - ETA: 0s - loss: 9.8352e-05 - mean_absolute_error: 0.0076 71/126 [===============>..............] - ETA: 0s - loss: 1.0303e-04 - mean_absolute_error: 0.0078 89/126 [====================>.........] - ETA: 0s - loss: 1.0535e-04 - mean_absolute_error: 0.0079107/126 [========================>.....] - ETA: 0s - loss: 1.0787e-04 - mean_absolute_error: 0.0080125/126 [============================>.] - ETA: 0s - loss: 1.0685e-04 - mean_absolute_error: 0.0079126/126 [==============================] - 0s 3ms/step - loss: 1.0671e-04 - mean_absolute_error: 0.0079 - val_loss: 1.5095e-04 - val_mean_absolute_error: 0.0100
Epoch 83/100
1/126 [..............................] - ETA: 0s - loss: 8.1198e-05 - mean_absolute_error: 0.0070 19/126 [===>..........................] - ETA: 0s - loss: 1.1906e-04 - mean_absolute_error: 0.0085 36/126 [=======>......................] - ETA: 0s - loss: 1.3347e-04 - mean_absolute_error: 0.0091 53/126 [===========>..................] - ETA: 0s - loss: 1.4241e-04 - mean_absolute_error: 0.0094 70/126 [===============>..............] - ETA: 0s - loss: 1.2743e-04 - mean_absolute_error: 0.0088 88/126 [===================>..........] - ETA: 0s - loss: 1.2663e-04 - mean_absolute_error: 0.0087105/126 [========================>.....] - ETA: 0s - loss: 1.2698e-04 - mean_absolute_error: 0.0087122/126 [============================>.] - ETA: 0s - loss: 1.2248e-04 - mean_absolute_error: 0.0085126/126 [==============================] - 0s 3ms/step - loss: 1.2153e-04 - mean_absolute_error: 0.0085 - val_loss: 1.0152e-04 - val_mean_absolute_error: 0.0079
Epoch 84/100
1/126 [..............................] - ETA: 0s - loss: 7.6185e-05 - mean_absolute_error: 0.0070 18/126 [===>..........................] - ETA: 0s - loss: 9.7716e-05 - mean_absolute_error: 0.0076 35/126 [=======>......................] - ETA: 0s - loss: 1.0475e-04 - mean_absolute_error: 0.0078 53/126 [===========>..................] - ETA: 0s - loss: 1.0271e-04 - mean_absolute_error: 0.0078 71/126 [===============>..............] - ETA: 0s - loss: 1.0441e-04 - mean_absolute_error: 0.0078 88/126 [===================>..........] - ETA: 0s - loss: 1.1046e-04 - mean_absolute_error: 0.0081104/126 [=======================>......] - ETA: 0s - loss: 1.1111e-04 - mean_absolute_error: 0.0081121/126 [===========================>..] - ETA: 0s - loss: 1.1050e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1038e-04 - mean_absolute_error: 0.0081 - val_loss: 1.7247e-04 - val_mean_absolute_error: 0.0106
Epoch 85/100
1/126 [..............................] - ETA: 0s - loss: 2.5979e-04 - mean_absolute_error: 0.0118 18/126 [===>..........................] - ETA: 0s - loss: 1.1340e-04 - mean_absolute_error: 0.0083 35/126 [=======>......................] - ETA: 0s - loss: 1.1643e-04 - mean_absolute_error: 0.0083 52/126 [===========>..................] - ETA: 0s - loss: 1.0929e-04 - mean_absolute_error: 0.0079 70/126 [===============>..............] - ETA: 0s - loss: 1.0685e-04 - mean_absolute_error: 0.0079 87/126 [===================>..........] - ETA: 0s - loss: 1.0364e-04 - mean_absolute_error: 0.0078104/126 [=======================>......] - ETA: 0s - loss: 1.1025e-04 - mean_absolute_error: 0.0080121/126 [===========================>..] - ETA: 0s - loss: 1.1148e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1046e-04 - mean_absolute_error: 0.0081 - val_loss: 1.2743e-04 - val_mean_absolute_error: 0.0091
Epoch 86/100
1/126 [..............................] - ETA: 0s - loss: 1.1129e-04 - mean_absolute_error: 0.0094 21/126 [====>.........................] - ETA: 0s - loss: 9.1172e-05 - mean_absolute_error: 0.0076 42/126 [=========>....................] - ETA: 0s - loss: 9.8796e-05 - mean_absolute_error: 0.0078 63/126 [==============>...............] - ETA: 0s - loss: 1.1056e-04 - mean_absolute_error: 0.0082 84/126 [===================>..........] - ETA: 0s - loss: 1.0844e-04 - mean_absolute_error: 0.0080105/126 [========================>.....] - ETA: 0s - loss: 1.1389e-04 - mean_absolute_error: 0.0082125/126 [============================>.] - ETA: 0s - loss: 1.1215e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1215e-04 - mean_absolute_error: 0.0081 - val_loss: 1.2118e-04 - val_mean_absolute_error: 0.0087
Epoch 87/100
1/126 [..............................] - ETA: 0s - loss: 6.9338e-05 - mean_absolute_error: 0.0071 22/126 [====>.........................] - ETA: 0s - loss: 1.1925e-04 - mean_absolute_error: 0.0087 43/126 [=========>....................] - ETA: 0s - loss: 1.1303e-04 - mean_absolute_error: 0.0083 64/126 [==============>...............] - ETA: 0s - loss: 1.0805e-04 - mean_absolute_error: 0.0081 85/126 [===================>..........] - ETA: 0s - loss: 1.0768e-04 - mean_absolute_error: 0.0080106/126 [========================>.....] - ETA: 0s - loss: 1.1111e-04 - mean_absolute_error: 0.0081126/126 [==============================] - ETA: 0s - loss: 1.1550e-04 - mean_absolute_error: 0.0083126/126 [==============================] - 0s 3ms/step - loss: 1.1550e-04 - mean_absolute_error: 0.0083 - val_loss: 3.4432e-04 - val_mean_absolute_error: 0.0163
Epoch 88/100
1/126 [..............................] - ETA: 0s - loss: 3.1322e-04 - mean_absolute_error: 0.0152 22/126 [====>.........................] - ETA: 0s - loss: 1.2472e-04 - mean_absolute_error: 0.0086 43/126 [=========>....................] - ETA: 0s - loss: 1.0623e-04 - mean_absolute_error: 0.0079 64/126 [==============>...............] - ETA: 0s - loss: 1.0429e-04 - mean_absolute_error: 0.0078 85/126 [===================>..........] - ETA: 0s - loss: 1.0169e-04 - mean_absolute_error: 0.0077106/126 [========================>.....] - ETA: 0s - loss: 9.8683e-05 - mean_absolute_error: 0.0075126/126 [==============================] - 0s 3ms/step - loss: 9.8693e-05 - mean_absolute_error: 0.0076 - val_loss: 9.7557e-05 - val_mean_absolute_error: 0.0076
Epoch 89/100
1/126 [..............................] - ETA: 0s - loss: 5.2576e-05 - mean_absolute_error: 0.0055 20/126 [===>..........................] - ETA: 0s - loss: 1.4284e-04 - mean_absolute_error: 0.0095 40/126 [========>.....................] - ETA: 0s - loss: 1.3982e-04 - mean_absolute_error: 0.0091 60/126 [=============>................] - ETA: 0s - loss: 1.2340e-04 - mean_absolute_error: 0.0085 81/126 [==================>...........] - ETA: 0s - loss: 1.1352e-04 - mean_absolute_error: 0.0081102/126 [=======================>......] - ETA: 0s - loss: 1.0936e-04 - mean_absolute_error: 0.0080123/126 [============================>.] - ETA: 0s - loss: 1.0401e-04 - mean_absolute_error: 0.0078126/126 [==============================] - 0s 3ms/step - loss: 1.0411e-04 - mean_absolute_error: 0.0078 - val_loss: 2.0561e-04 - val_mean_absolute_error: 0.0117
Epoch 90/100
1/126 [..............................] - ETA: 0s - loss: 1.3298e-04 - mean_absolute_error: 0.0094 22/126 [====>.........................] - ETA: 0s - loss: 1.0200e-04 - mean_absolute_error: 0.0077 43/126 [=========>....................] - ETA: 0s - loss: 9.6225e-05 - mean_absolute_error: 0.0075 64/126 [==============>...............] - ETA: 0s - loss: 9.8436e-05 - mean_absolute_error: 0.0076 85/126 [===================>..........] - ETA: 0s - loss: 9.5200e-05 - mean_absolute_error: 0.0075106/126 [========================>.....] - ETA: 0s - loss: 9.3790e-05 - mean_absolute_error: 0.0074126/126 [==============================] - 0s 3ms/step - loss: 9.6144e-05 - mean_absolute_error: 0.0074 - val_loss: 1.0244e-04 - val_mean_absolute_error: 0.0079
Epoch 91/100
1/126 [..............................] - ETA: 0s - loss: 8.2370e-05 - mean_absolute_error: 0.0068 22/126 [====>.........................] - ETA: 0s - loss: 8.9001e-05 - mean_absolute_error: 0.0070 43/126 [=========>....................] - ETA: 0s - loss: 9.3217e-05 - mean_absolute_error: 0.0071 64/126 [==============>...............] - ETA: 0s - loss: 9.4183e-05 - mean_absolute_error: 0.0073 85/126 [===================>..........] - ETA: 0s - loss: 9.5640e-05 - mean_absolute_error: 0.0074105/126 [========================>.....] - ETA: 0s - loss: 9.5976e-05 - mean_absolute_error: 0.0074125/126 [============================>.] - ETA: 0s - loss: 1.0015e-04 - mean_absolute_error: 0.0076126/126 [==============================] - 0s 3ms/step - loss: 1.0007e-04 - mean_absolute_error: 0.0076 - val_loss: 1.0092e-04 - val_mean_absolute_error: 0.0078
Epoch 92/100
1/126 [..............................] - ETA: 0s - loss: 4.2239e-05 - mean_absolute_error: 0.0050 22/126 [====>.........................] - ETA: 0s - loss: 1.1576e-04 - mean_absolute_error: 0.0086 42/126 [=========>....................] - ETA: 0s - loss: 1.2552e-04 - mean_absolute_error: 0.0089 62/126 [=============>................] - ETA: 0s - loss: 1.2491e-04 - mean_absolute_error: 0.0087 83/126 [==================>...........] - ETA: 0s - loss: 1.1620e-04 - mean_absolute_error: 0.0083103/126 [=======================>......] - ETA: 0s - loss: 1.1210e-04 - mean_absolute_error: 0.0082124/126 [============================>.] - ETA: 0s - loss: 1.0872e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.0833e-04 - mean_absolute_error: 0.0081 - val_loss: 1.2023e-04 - val_mean_absolute_error: 0.0088
Epoch 93/100
1/126 [..............................] - ETA: 0s - loss: 8.3534e-05 - mean_absolute_error: 0.0070 21/126 [====>.........................] - ETA: 0s - loss: 7.8656e-05 - mean_absolute_error: 0.0068 41/126 [========>.....................] - ETA: 0s - loss: 8.4392e-05 - mean_absolute_error: 0.0070 61/126 [=============>................] - ETA: 0s - loss: 9.2554e-05 - mean_absolute_error: 0.0073 81/126 [==================>...........] - ETA: 0s - loss: 9.8514e-05 - mean_absolute_error: 0.0075102/126 [=======================>......] - ETA: 0s - loss: 9.5155e-05 - mean_absolute_error: 0.0074122/126 [============================>.] - ETA: 0s - loss: 9.7656e-05 - mean_absolute_error: 0.0075126/126 [==============================] - 0s 3ms/step - loss: 9.8680e-05 - mean_absolute_error: 0.0075 - val_loss: 1.1053e-04 - val_mean_absolute_error: 0.0084
Epoch 94/100
1/126 [..............................] - ETA: 0s - loss: 1.4261e-04 - mean_absolute_error: 0.0086 22/126 [====>.........................] - ETA: 0s - loss: 1.0437e-04 - mean_absolute_error: 0.0078 43/126 [=========>....................] - ETA: 0s - loss: 1.0942e-04 - mean_absolute_error: 0.0081 64/126 [==============>...............] - ETA: 0s - loss: 1.1766e-04 - mean_absolute_error: 0.0084 85/126 [===================>..........] - ETA: 0s - loss: 1.2234e-04 - mean_absolute_error: 0.0086106/126 [========================>.....] - ETA: 0s - loss: 1.1816e-04 - mean_absolute_error: 0.0084126/126 [==============================] - ETA: 0s - loss: 1.1372e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 0s 3ms/step - loss: 1.1372e-04 - mean_absolute_error: 0.0082 - val_loss: 1.3433e-04 - val_mean_absolute_error: 0.0093
Epoch 95/100
1/126 [..............................] - ETA: 0s - loss: 8.9143e-05 - mean_absolute_error: 0.0078 22/126 [====>.........................] - ETA: 0s - loss: 1.1673e-04 - mean_absolute_error: 0.0083 43/126 [=========>....................] - ETA: 0s - loss: 1.2758e-04 - mean_absolute_error: 0.0089 64/126 [==============>...............] - ETA: 0s - loss: 1.2132e-04 - mean_absolute_error: 0.0086 84/126 [===================>..........] - ETA: 0s - loss: 1.1823e-04 - mean_absolute_error: 0.0084104/126 [=======================>......] - ETA: 0s - loss: 1.2086e-04 - mean_absolute_error: 0.0085124/126 [============================>.] - ETA: 0s - loss: 1.1657e-04 - mean_absolute_error: 0.0084126/126 [==============================] - 0s 3ms/step - loss: 1.1597e-04 - mean_absolute_error: 0.0083 - val_loss: 1.0057e-04 - val_mean_absolute_error: 0.0079
Epoch 96/100
1/126 [..............................] - ETA: 0s - loss: 9.9872e-05 - mean_absolute_error: 0.0079 23/126 [====>.........................] - ETA: 0s - loss: 9.2616e-05 - mean_absolute_error: 0.0073 44/126 [=========>....................] - ETA: 0s - loss: 9.3609e-05 - mean_absolute_error: 0.0074 65/126 [==============>...............] - ETA: 0s - loss: 9.3528e-05 - mean_absolute_error: 0.0074 86/126 [===================>..........] - ETA: 0s - loss: 9.4966e-05 - mean_absolute_error: 0.0074107/126 [========================>.....] - ETA: 0s - loss: 9.6736e-05 - mean_absolute_error: 0.0075126/126 [==============================] - 0s 3ms/step - loss: 9.4026e-05 - mean_absolute_error: 0.0074 - val_loss: 1.3510e-04 - val_mean_absolute_error: 0.0093
Epoch 97/100
1/126 [..............................] - ETA: 0s - loss: 1.1601e-04 - mean_absolute_error: 0.0087 22/126 [====>.........................] - ETA: 0s - loss: 1.0764e-04 - mean_absolute_error: 0.0081 43/126 [=========>....................] - ETA: 0s - loss: 1.1077e-04 - mean_absolute_error: 0.0080 64/126 [==============>...............] - ETA: 0s - loss: 1.0265e-04 - mean_absolute_error: 0.0077 85/126 [===================>..........] - ETA: 0s - loss: 9.8843e-05 - mean_absolute_error: 0.0076106/126 [========================>.....] - ETA: 0s - loss: 9.9931e-05 - mean_absolute_error: 0.0077126/126 [==============================] - 0s 3ms/step - loss: 9.9288e-05 - mean_absolute_error: 0.0076 - val_loss: 1.0404e-04 - val_mean_absolute_error: 0.0080
Epoch 98/100
1/126 [..............................] - ETA: 0s - loss: 8.3702e-05 - mean_absolute_error: 0.0071 22/126 [====>.........................] - ETA: 0s - loss: 1.1807e-04 - mean_absolute_error: 0.0083 43/126 [=========>....................] - ETA: 0s - loss: 1.0881e-04 - mean_absolute_error: 0.0079 64/126 [==============>...............] - ETA: 0s - loss: 1.0992e-04 - mean_absolute_error: 0.0080 85/126 [===================>..........] - ETA: 0s - loss: 1.1334e-04 - mean_absolute_error: 0.0082106/126 [========================>.....] - ETA: 0s - loss: 1.1153e-04 - mean_absolute_error: 0.0081126/126 [==============================] - ETA: 0s - loss: 1.1438e-04 - mean_absolute_error: 0.0082126/126 [==============================] - 0s 3ms/step - loss: 1.1438e-04 - mean_absolute_error: 0.0082 - val_loss: 1.5167e-04 - val_mean_absolute_error: 0.0098
Epoch 99/100
1/126 [..............................] - ETA: 0s - loss: 8.8293e-05 - mean_absolute_error: 0.0072 22/126 [====>.........................] - ETA: 0s - loss: 1.0637e-04 - mean_absolute_error: 0.0077 43/126 [=========>....................] - ETA: 0s - loss: 1.0910e-04 - mean_absolute_error: 0.0079 64/126 [==============>...............] - ETA: 0s - loss: 1.0478e-04 - mean_absolute_error: 0.0078 85/126 [===================>..........] - ETA: 0s - loss: 1.1351e-04 - mean_absolute_error: 0.0082106/126 [========================>.....] - ETA: 0s - loss: 1.1755e-04 - mean_absolute_error: 0.0084126/126 [==============================] - 0s 3ms/step - loss: 1.2193e-04 - mean_absolute_error: 0.0086 - val_loss: 1.5336e-04 - val_mean_absolute_error: 0.0099
Epoch 100/100
1/126 [..............................] - ETA: 0s - loss: 1.2522e-04 - mean_absolute_error: 0.0094 22/126 [====>.........................] - ETA: 0s - loss: 1.1204e-04 - mean_absolute_error: 0.0084 43/126 [=========>....................] - ETA: 0s - loss: 1.1362e-04 - mean_absolute_error: 0.0082 64/126 [==============>...............] - ETA: 0s - loss: 1.1794e-04 - mean_absolute_error: 0.0084 85/126 [===================>..........] - ETA: 0s - loss: 1.1242e-04 - mean_absolute_error: 0.0081106/126 [========================>.....] - ETA: 0s - loss: 1.0643e-04 - mean_absolute_error: 0.0079126/126 [==============================] - 0s 3ms/step - loss: 1.0335e-04 - mean_absolute_error: 0.0078 - val_loss: 1.0612e-04 - val_mean_absolute_error: 0.0081
<keras.src.callbacks.History at 0x1b9b0619590>
After the training and fitting of the Machine Learning model for Canada, I tried to create visualizations comparing the model against the country’s training dataset, validation dataset, but most importantly the testing dataset (as shown below in the line graphs). Note that the darker and thicker blue lines represent the prediction model’s projections and the thinner red lines is the observed/gathered data.
```{python}
# Testing the Machine Learning Model prediction for Austrailia with the train,
# validation, and test sets
# Most important is the test set prediction as this tests the effectiveness
# of the Machine Learning model on data it has not seen before
canada_train_pred = canada_model.predict(X_canada_train).flatten()
plt.plot(dates_canada_train, canada_train_pred, linewidth=4)
plt.plot(dates_canada_train, y_canada_train, linewidth=1)
plt.legend(["Training Predictions", "Training Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Canada - Training Set Predictions vs. Observations")
plt.show()
canada_val_pred = canada_model.predict(X_canada_val).flatten()
plt.plot(dates_canada_val, canada_val_pred, linewidth=4)
plt.plot(dates_canada_val, y_canada_val, linewidth=1)
plt.legend(["Validation Predictions", "Validation Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Canada - Validation Set Predictions vs. Observations")
plt.show()
canada_test_pred = canada_model.predict(X_canada_test).flatten()
plt.plot(dates_canada_test, canada_test_pred, linewidth=4)
plt.plot(dates_canada_test, y_canada_test, linewidth=1)
plt.legend(["Testing Predictions", "Testing Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Canada - Testing Set Predictions vs. Observations")
plt.show()
``` 1/126 [..............................] - ETA: 42s 41/126 [========>.....................] - ETA: 0s 81/126 [==================>...........] - ETA: 0s122/126 [============================>.] - ETA: 0s126/126 [==============================] - 1s 1ms/step
1/16 [>.............................] - ETA: 0s16/16 [==============================] - 0s 1ms/step
1/16 [>.............................] - ETA: 0s16/16 [==============================] - 0s 1ms/step
Through careful consideration of all of the prediction-based vs. observation-based contrast visualizations together, I consolidated all of graphics into one singular visualization for you to see below to get a more general perspective of the effectiveness of the Machine Learning model at training and fitting towards predicting Canada’s international currency rate with the United States.
```{python}
# Plotting Canada's observational (reference) data with the predictions of its
# Machine Learning Model (as a way to visually inspect the effectiveness of the
# model)
plt.plot(dates_canada_train, canada_train_pred, linewidth=4)
plt.plot(dates_canada_train, y_canada_train, linewidth=1)
plt.plot(dates_canada_val, canada_val_pred, linewidth=4)
plt.plot(dates_canada_val, y_canada_val, linewidth=1)
plt.plot(dates_canada_test, canada_test_pred, linewidth=4)
plt.plot(dates_canada_test, y_canada_test, linewidth=1)
plt.legend(["Training Predictions",
"Training Observations",
"Validation Predictions",
"Validation Observations",
"Testing Predictions",
"Testing Observations"], loc="upper right")
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Culmination of the Three Machine Learning Phases of Austrailia's Dataset - Predictions vs. Observations")
plt.show()
```Then, I worked on the United Kingdom’s data (as shown below):
Since the data (date, X, and y) is split into three np.arrays and to be more efficient, I will manually split the United Kingdom’s data into train, test, and validation datasets for the Machine Learning model with 80% going to the training dataset, the next 10% going to the validation dataset, and the last 10% going to the test dataset for each np.array respectively.
```{python}
# Splitting United Kingdom's data into train, test, and validation sets on 3
# mediums: the X-axis, the y-axis, and the indices (represented by dates)
dates_united_kingdom_train, X_united_kingdom_train, y_united_kingdom_train = dates_united_kingdom[:percentile_80], X_united_kingdom[:percentile_80], y_united_kingdom[:percentile_80]
dates_united_kingdom_val, X_united_kingdom_val, y_united_kingdom_val = dates_united_kingdom[percentile_80:percentile_90], X_united_kingdom[percentile_80:percentile_90], y_united_kingdom[percentile_80:percentile_90]
dates_united_kingdom_test, X_united_kingdom_test, y_united_kingdom_test = dates_united_kingdom[percentile_90:], X_united_kingdom[percentile_90:], y_united_kingdom[percentile_90:]
plt.plot(dates_united_kingdom_train, y_united_kingdom_train, linewidth=1)
plt.plot(dates_united_kingdom_val, y_united_kingdom_val, linewidth=1)
plt.plot(dates_united_kingdom_test, y_united_kingdom_test, linewidth=1)
plt.legend(["Training", "Validation", "Testing"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Split of United Kingdom's Data for LSTM Model")
plt.show()
```Now, I began to configure the Machine Learning model. We added Sequential layers: an Input layer 3 by 1 because we will have 3 np.arrays of Input and 1 np.array as output, utilize a LSTM (Long Short-Term Memory) layer of 64 neurons, apply 2 levels of dense layers with 32 neurons and folliowing recommendations online to use the RELU (Rectified Linear Unit) Activiation Function, and I followed up with one last dense layer of 1 neuron as our output layer since we are just trying to linearly-predict the next currency-rate on a near-future date. Once I configured the Sequential layers, we are ready to compile the model, utilzing the mean_square_error as our minimizing loss function, using the Adam optimizer, and comparing our trained model against our data with the mean_absolute_error metric. Lastly, I fitted our model, utilzing our X_train and Y_train datasets for fitting with validation from our X_valid and Y_valid datasets at 100 epochs.
```{python}
# Configuring the Machine Learning Tensorflow Model for United Kingdom
united_kingdom_model = Sequential([layers.Input((3, 1)),
layers.LSTM(64),
layers.Dense(32, activation="relu"),
layers.Dense(32, activation="relu"),
layers.Dense(1)])
united_kingdom_model.compile(loss="mse",
optimizer=Adam(learning_rate=0.001),
metrics=["mean_absolute_error"])
united_kingdom_model.fit(X_united_kingdom_train, y_united_kingdom_train, validation_data=(X_united_kingdom_val, y_united_kingdom_val), epochs=100)
```Epoch 1/100
1/126 [..............................] - ETA: 4:07 - loss: 0.3905 - mean_absolute_error: 0.6227 23/126 [====>.........................] - ETA: 0s - loss: 0.2156 - mean_absolute_error: 0.4488 45/126 [=========>....................] - ETA: 0s - loss: 0.1158 - mean_absolute_error: 0.2754 66/126 [==============>...............] - ETA: 0s - loss: 0.0795 - mean_absolute_error: 0.1984 86/126 [===================>..........] - ETA: 0s - loss: 0.0612 - mean_absolute_error: 0.1574107/126 [========================>.....] - ETA: 0s - loss: 0.0493 - mean_absolute_error: 0.1307126/126 [==============================] - 3s 6ms/step - loss: 0.0422 - mean_absolute_error: 0.1147 - val_loss: 0.0036 - val_mean_absolute_error: 0.0574
Epoch 2/100
1/126 [..............................] - ETA: 0s - loss: 7.4259e-04 - mean_absolute_error: 0.0235 24/126 [====>.........................] - ETA: 0s - loss: 6.0324e-04 - mean_absolute_error: 0.0195 47/126 [==========>...................] - ETA: 0s - loss: 6.2308e-04 - mean_absolute_error: 0.0201 69/126 [===============>..............] - ETA: 0s - loss: 6.1058e-04 - mean_absolute_error: 0.0200 91/126 [====================>.........] - ETA: 0s - loss: 5.9400e-04 - mean_absolute_error: 0.0197113/126 [=========================>....] - ETA: 0s - loss: 5.8642e-04 - mean_absolute_error: 0.0197126/126 [==============================] - 0s 3ms/step - loss: 5.7809e-04 - mean_absolute_error: 0.0195 - val_loss: 0.0027 - val_mean_absolute_error: 0.0494
Epoch 3/100
1/126 [..............................] - ETA: 0s - loss: 5.4789e-04 - mean_absolute_error: 0.0204 23/126 [====>.........................] - ETA: 0s - loss: 4.7826e-04 - mean_absolute_error: 0.0177 45/126 [=========>....................] - ETA: 0s - loss: 4.7430e-04 - mean_absolute_error: 0.0177 67/126 [==============>...............] - ETA: 0s - loss: 4.6772e-04 - mean_absolute_error: 0.0176 88/126 [===================>..........] - ETA: 0s - loss: 4.5642e-04 - mean_absolute_error: 0.0174109/126 [========================>.....] - ETA: 0s - loss: 4.4781e-04 - mean_absolute_error: 0.0172126/126 [==============================] - 0s 3ms/step - loss: 4.3484e-04 - mean_absolute_error: 0.0169 - val_loss: 0.0019 - val_mean_absolute_error: 0.0419
Epoch 4/100
1/126 [..............................] - ETA: 0s - loss: 3.5392e-04 - mean_absolute_error: 0.0164 23/126 [====>.........................] - ETA: 0s - loss: 3.4229e-04 - mean_absolute_error: 0.0149 43/126 [=========>....................] - ETA: 0s - loss: 3.3125e-04 - mean_absolute_error: 0.0146 61/126 [=============>................] - ETA: 0s - loss: 3.3049e-04 - mean_absolute_error: 0.0147 81/126 [==================>...........] - ETA: 0s - loss: 3.1816e-04 - mean_absolute_error: 0.0144102/126 [=======================>......] - ETA: 0s - loss: 3.0277e-04 - mean_absolute_error: 0.0140123/126 [============================>.] - ETA: 0s - loss: 2.9131e-04 - mean_absolute_error: 0.0137126/126 [==============================] - 0s 3ms/step - loss: 2.8927e-04 - mean_absolute_error: 0.0137 - val_loss: 0.0011 - val_mean_absolute_error: 0.0319
Epoch 5/100
1/126 [..............................] - ETA: 0s - loss: 2.0565e-04 - mean_absolute_error: 0.0118 22/126 [====>.........................] - ETA: 0s - loss: 2.2461e-04 - mean_absolute_error: 0.0121 44/126 [=========>....................] - ETA: 0s - loss: 2.1029e-04 - mean_absolute_error: 0.0117 65/126 [==============>...............] - ETA: 0s - loss: 1.9104e-04 - mean_absolute_error: 0.0111 86/126 [===================>..........] - ETA: 0s - loss: 1.8318e-04 - mean_absolute_error: 0.0109107/126 [========================>.....] - ETA: 0s - loss: 1.7509e-04 - mean_absolute_error: 0.0106126/126 [==============================] - 0s 3ms/step - loss: 1.6767e-04 - mean_absolute_error: 0.0104 - val_loss: 3.1902e-04 - val_mean_absolute_error: 0.0157
Epoch 6/100
1/126 [..............................] - ETA: 0s - loss: 1.3014e-04 - mean_absolute_error: 0.0091 23/126 [====>.........................] - ETA: 0s - loss: 1.2154e-04 - mean_absolute_error: 0.0090 44/126 [=========>....................] - ETA: 0s - loss: 1.0866e-04 - mean_absolute_error: 0.0084 65/126 [==============>...............] - ETA: 0s - loss: 1.0130e-04 - mean_absolute_error: 0.0080 87/126 [===================>..........] - ETA: 0s - loss: 9.4647e-05 - mean_absolute_error: 0.0078109/126 [========================>.....] - ETA: 0s - loss: 8.8740e-05 - mean_absolute_error: 0.0075126/126 [==============================] - 0s 3ms/step - loss: 8.6031e-05 - mean_absolute_error: 0.0073 - val_loss: 1.5289e-04 - val_mean_absolute_error: 0.0101
Epoch 7/100
1/126 [..............................] - ETA: 0s - loss: 4.8239e-05 - mean_absolute_error: 0.0055 22/126 [====>.........................] - ETA: 0s - loss: 5.0919e-05 - mean_absolute_error: 0.0056 43/126 [=========>....................] - ETA: 0s - loss: 5.3793e-05 - mean_absolute_error: 0.0056 64/126 [==============>...............] - ETA: 0s - loss: 5.1699e-05 - mean_absolute_error: 0.0055 85/126 [===================>..........] - ETA: 0s - loss: 5.0261e-05 - mean_absolute_error: 0.0055106/126 [========================>.....] - ETA: 0s - loss: 4.8852e-05 - mean_absolute_error: 0.0054126/126 [==============================] - 0s 3ms/step - loss: 4.8369e-05 - mean_absolute_error: 0.0053 - val_loss: 7.2417e-05 - val_mean_absolute_error: 0.0060
Epoch 8/100
1/126 [..............................] - ETA: 0s - loss: 2.3990e-05 - mean_absolute_error: 0.0034 23/126 [====>.........................] - ETA: 0s - loss: 4.0440e-05 - mean_absolute_error: 0.0047 45/126 [=========>....................] - ETA: 0s - loss: 3.8657e-05 - mean_absolute_error: 0.0046 67/126 [==============>...............] - ETA: 0s - loss: 3.6133e-05 - mean_absolute_error: 0.0045 88/126 [===================>..........] - ETA: 0s - loss: 3.6391e-05 - mean_absolute_error: 0.0045109/126 [========================>.....] - ETA: 0s - loss: 3.7519e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 3.7663e-05 - mean_absolute_error: 0.0045 - val_loss: 7.3828e-05 - val_mean_absolute_error: 0.0062
Epoch 9/100
1/126 [..............................] - ETA: 0s - loss: 3.5898e-05 - mean_absolute_error: 0.0046 23/126 [====>.........................] - ETA: 0s - loss: 3.8815e-05 - mean_absolute_error: 0.0045 45/126 [=========>....................] - ETA: 0s - loss: 3.7708e-05 - mean_absolute_error: 0.0045 67/126 [==============>...............] - ETA: 0s - loss: 3.5987e-05 - mean_absolute_error: 0.0043 89/126 [====================>.........] - ETA: 0s - loss: 3.6648e-05 - mean_absolute_error: 0.0043111/126 [=========================>....] - ETA: 0s - loss: 3.6268e-05 - mean_absolute_error: 0.0043126/126 [==============================] - 0s 3ms/step - loss: 3.5587e-05 - mean_absolute_error: 0.0043 - val_loss: 9.6980e-05 - val_mean_absolute_error: 0.0077
Epoch 10/100
1/126 [..............................] - ETA: 0s - loss: 2.7448e-05 - mean_absolute_error: 0.0039 22/126 [====>.........................] - ETA: 0s - loss: 3.4995e-05 - mean_absolute_error: 0.0044 44/126 [=========>....................] - ETA: 0s - loss: 3.9000e-05 - mean_absolute_error: 0.0045 65/126 [==============>...............] - ETA: 0s - loss: 3.8066e-05 - mean_absolute_error: 0.0045 87/126 [===================>..........] - ETA: 0s - loss: 3.6903e-05 - mean_absolute_error: 0.0044108/126 [========================>.....] - ETA: 0s - loss: 3.6319e-05 - mean_absolute_error: 0.0043126/126 [==============================] - 0s 3ms/step - loss: 3.5593e-05 - mean_absolute_error: 0.0043 - val_loss: 9.2268e-05 - val_mean_absolute_error: 0.0074
Epoch 11/100
1/126 [..............................] - ETA: 0s - loss: 2.8719e-05 - mean_absolute_error: 0.0039 23/126 [====>.........................] - ETA: 0s - loss: 4.0883e-05 - mean_absolute_error: 0.0046 44/126 [=========>....................] - ETA: 0s - loss: 3.5849e-05 - mean_absolute_error: 0.0044 66/126 [==============>...............] - ETA: 0s - loss: 3.5461e-05 - mean_absolute_error: 0.0044 87/126 [===================>..........] - ETA: 0s - loss: 3.6309e-05 - mean_absolute_error: 0.0045108/126 [========================>.....] - ETA: 0s - loss: 3.6658e-05 - mean_absolute_error: 0.0044126/126 [==============================] - 0s 3ms/step - loss: 3.7287e-05 - mean_absolute_error: 0.0045 - val_loss: 7.3156e-05 - val_mean_absolute_error: 0.0060
Epoch 12/100
1/126 [..............................] - ETA: 0s - loss: 4.0655e-05 - mean_absolute_error: 0.0050 23/126 [====>.........................] - ETA: 0s - loss: 4.4123e-05 - mean_absolute_error: 0.0048 45/126 [=========>....................] - ETA: 0s - loss: 3.8753e-05 - mean_absolute_error: 0.0045 67/126 [==============>...............] - ETA: 0s - loss: 3.8085e-05 - mean_absolute_error: 0.0045 89/126 [====================>.........] - ETA: 0s - loss: 3.8123e-05 - mean_absolute_error: 0.0045110/126 [=========================>....] - ETA: 0s - loss: 3.7217e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.6841e-05 - mean_absolute_error: 0.0044 - val_loss: 8.9902e-05 - val_mean_absolute_error: 0.0072
Epoch 13/100
1/126 [..............................] - ETA: 0s - loss: 1.5089e-05 - mean_absolute_error: 0.0023 22/126 [====>.........................] - ETA: 0s - loss: 3.1067e-05 - mean_absolute_error: 0.0040 44/126 [=========>....................] - ETA: 0s - loss: 3.0184e-05 - mean_absolute_error: 0.0039 66/126 [==============>...............] - ETA: 0s - loss: 3.2228e-05 - mean_absolute_error: 0.0040 87/126 [===================>..........] - ETA: 0s - loss: 3.3662e-05 - mean_absolute_error: 0.0042108/126 [========================>.....] - ETA: 0s - loss: 3.4800e-05 - mean_absolute_error: 0.0043126/126 [==============================] - 0s 3ms/step - loss: 3.6129e-05 - mean_absolute_error: 0.0044 - val_loss: 1.0178e-04 - val_mean_absolute_error: 0.0079
Epoch 14/100
1/126 [..............................] - ETA: 0s - loss: 2.9505e-05 - mean_absolute_error: 0.0042 22/126 [====>.........................] - ETA: 0s - loss: 3.7624e-05 - mean_absolute_error: 0.0048 44/126 [=========>....................] - ETA: 0s - loss: 3.9061e-05 - mean_absolute_error: 0.0048 66/126 [==============>...............] - ETA: 0s - loss: 3.7643e-05 - mean_absolute_error: 0.0047 87/126 [===================>..........] - ETA: 0s - loss: 3.8554e-05 - mean_absolute_error: 0.0047108/126 [========================>.....] - ETA: 0s - loss: 3.8058e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 3.7475e-05 - mean_absolute_error: 0.0045 - val_loss: 7.8812e-05 - val_mean_absolute_error: 0.0065
Epoch 15/100
1/126 [..............................] - ETA: 0s - loss: 1.8000e-05 - mean_absolute_error: 0.0031 23/126 [====>.........................] - ETA: 0s - loss: 3.5953e-05 - mean_absolute_error: 0.0044 45/126 [=========>....................] - ETA: 0s - loss: 3.5044e-05 - mean_absolute_error: 0.0042 67/126 [==============>...............] - ETA: 0s - loss: 3.5658e-05 - mean_absolute_error: 0.0043 88/126 [===================>..........] - ETA: 0s - loss: 3.6771e-05 - mean_absolute_error: 0.0045110/126 [=========================>....] - ETA: 0s - loss: 3.7356e-05 - mean_absolute_error: 0.0044126/126 [==============================] - 0s 3ms/step - loss: 3.6703e-05 - mean_absolute_error: 0.0044 - val_loss: 1.1797e-04 - val_mean_absolute_error: 0.0087
Epoch 16/100
1/126 [..............................] - ETA: 0s - loss: 3.8566e-05 - mean_absolute_error: 0.0051 23/126 [====>.........................] - ETA: 0s - loss: 3.5735e-05 - mean_absolute_error: 0.0044 45/126 [=========>....................] - ETA: 0s - loss: 3.9238e-05 - mean_absolute_error: 0.0045 67/126 [==============>...............] - ETA: 0s - loss: 3.9853e-05 - mean_absolute_error: 0.0046 88/126 [===================>..........] - ETA: 0s - loss: 3.8955e-05 - mean_absolute_error: 0.0046109/126 [========================>.....] - ETA: 0s - loss: 3.7896e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.7078e-05 - mean_absolute_error: 0.0045 - val_loss: 8.2179e-05 - val_mean_absolute_error: 0.0067
Epoch 17/100
1/126 [..............................] - ETA: 0s - loss: 2.4024e-05 - mean_absolute_error: 0.0035 23/126 [====>.........................] - ETA: 0s - loss: 3.2944e-05 - mean_absolute_error: 0.0042 45/126 [=========>....................] - ETA: 0s - loss: 3.8476e-05 - mean_absolute_error: 0.0047 67/126 [==============>...............] - ETA: 0s - loss: 4.0984e-05 - mean_absolute_error: 0.0049 88/126 [===================>..........] - ETA: 0s - loss: 4.0847e-05 - mean_absolute_error: 0.0048110/126 [=========================>....] - ETA: 0s - loss: 3.9923e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 3.9527e-05 - mean_absolute_error: 0.0047 - val_loss: 7.2796e-05 - val_mean_absolute_error: 0.0061
Epoch 18/100
1/126 [..............................] - ETA: 0s - loss: 2.8707e-05 - mean_absolute_error: 0.0043 23/126 [====>.........................] - ETA: 0s - loss: 3.5218e-05 - mean_absolute_error: 0.0042 45/126 [=========>....................] - ETA: 0s - loss: 3.5532e-05 - mean_absolute_error: 0.0042 67/126 [==============>...............] - ETA: 0s - loss: 3.5899e-05 - mean_absolute_error: 0.0043 89/126 [====================>.........] - ETA: 0s - loss: 3.5280e-05 - mean_absolute_error: 0.0043109/126 [========================>.....] - ETA: 0s - loss: 3.5431e-05 - mean_absolute_error: 0.0043126/126 [==============================] - 0s 3ms/step - loss: 3.6811e-05 - mean_absolute_error: 0.0044 - val_loss: 7.7296e-05 - val_mean_absolute_error: 0.0065
Epoch 19/100
1/126 [..............................] - ETA: 0s - loss: 6.8337e-05 - mean_absolute_error: 0.0060 23/126 [====>.........................] - ETA: 0s - loss: 3.9330e-05 - mean_absolute_error: 0.0046 45/126 [=========>....................] - ETA: 0s - loss: 3.7610e-05 - mean_absolute_error: 0.0045 67/126 [==============>...............] - ETA: 0s - loss: 3.7199e-05 - mean_absolute_error: 0.0045 89/126 [====================>.........] - ETA: 0s - loss: 3.6851e-05 - mean_absolute_error: 0.0045110/126 [=========================>....] - ETA: 0s - loss: 3.7193e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.7554e-05 - mean_absolute_error: 0.0045 - val_loss: 9.2006e-05 - val_mean_absolute_error: 0.0074
Epoch 20/100
1/126 [..............................] - ETA: 0s - loss: 3.0088e-05 - mean_absolute_error: 0.0042 23/126 [====>.........................] - ETA: 0s - loss: 3.7265e-05 - mean_absolute_error: 0.0044 45/126 [=========>....................] - ETA: 0s - loss: 3.4926e-05 - mean_absolute_error: 0.0043 67/126 [==============>...............] - ETA: 0s - loss: 3.5192e-05 - mean_absolute_error: 0.0043 88/126 [===================>..........] - ETA: 0s - loss: 3.7112e-05 - mean_absolute_error: 0.0045106/126 [========================>.....] - ETA: 0s - loss: 3.7236e-05 - mean_absolute_error: 0.0045125/126 [============================>.] - ETA: 0s - loss: 3.6754e-05 - mean_absolute_error: 0.0044126/126 [==============================] - 0s 3ms/step - loss: 3.6749e-05 - mean_absolute_error: 0.0044 - val_loss: 8.9647e-05 - val_mean_absolute_error: 0.0073
Epoch 21/100
1/126 [..............................] - ETA: 0s - loss: 3.1421e-05 - mean_absolute_error: 0.0039 19/126 [===>..........................] - ETA: 0s - loss: 3.3327e-05 - mean_absolute_error: 0.0043 37/126 [=======>......................] - ETA: 0s - loss: 3.2472e-05 - mean_absolute_error: 0.0042 57/126 [============>.................] - ETA: 0s - loss: 3.5845e-05 - mean_absolute_error: 0.0044 77/126 [=================>............] - ETA: 0s - loss: 3.7019e-05 - mean_absolute_error: 0.0045 98/126 [======================>.......] - ETA: 0s - loss: 3.6350e-05 - mean_absolute_error: 0.0045119/126 [===========================>..] - ETA: 0s - loss: 3.7244e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.7208e-05 - mean_absolute_error: 0.0045 - val_loss: 7.2080e-05 - val_mean_absolute_error: 0.0061
Epoch 22/100
1/126 [..............................] - ETA: 0s - loss: 2.7621e-05 - mean_absolute_error: 0.0041 23/126 [====>.........................] - ETA: 0s - loss: 3.1498e-05 - mean_absolute_error: 0.0041 45/126 [=========>....................] - ETA: 0s - loss: 3.3107e-05 - mean_absolute_error: 0.0042 66/126 [==============>...............] - ETA: 0s - loss: 3.5259e-05 - mean_absolute_error: 0.0043 88/126 [===================>..........] - ETA: 0s - loss: 3.5813e-05 - mean_absolute_error: 0.0044109/126 [========================>.....] - ETA: 0s - loss: 3.6434e-05 - mean_absolute_error: 0.0044126/126 [==============================] - 0s 3ms/step - loss: 3.6297e-05 - mean_absolute_error: 0.0044 - val_loss: 7.0195e-05 - val_mean_absolute_error: 0.0058
Epoch 23/100
1/126 [..............................] - ETA: 0s - loss: 2.6784e-05 - mean_absolute_error: 0.0044 21/126 [====>.........................] - ETA: 0s - loss: 4.2064e-05 - mean_absolute_error: 0.0048 41/126 [========>.....................] - ETA: 0s - loss: 4.2145e-05 - mean_absolute_error: 0.0047 61/126 [=============>................] - ETA: 0s - loss: 4.1268e-05 - mean_absolute_error: 0.0047 81/126 [==================>...........] - ETA: 0s - loss: 3.9766e-05 - mean_absolute_error: 0.0046101/126 [=======================>......] - ETA: 0s - loss: 3.7716e-05 - mean_absolute_error: 0.0045121/126 [===========================>..] - ETA: 0s - loss: 3.6925e-05 - mean_absolute_error: 0.0044126/126 [==============================] - 0s 3ms/step - loss: 3.6713e-05 - mean_absolute_error: 0.0044 - val_loss: 7.5646e-05 - val_mean_absolute_error: 0.0064
Epoch 24/100
1/126 [..............................] - ETA: 0s - loss: 3.9011e-05 - mean_absolute_error: 0.0047 22/126 [====>.........................] - ETA: 0s - loss: 2.9107e-05 - mean_absolute_error: 0.0040 42/126 [=========>....................] - ETA: 0s - loss: 3.3873e-05 - mean_absolute_error: 0.0043 64/126 [==============>...............] - ETA: 0s - loss: 3.6573e-05 - mean_absolute_error: 0.0044 86/126 [===================>..........] - ETA: 0s - loss: 3.6506e-05 - mean_absolute_error: 0.0044107/126 [========================>.....] - ETA: 0s - loss: 3.6596e-05 - mean_absolute_error: 0.0044126/126 [==============================] - 0s 3ms/step - loss: 3.6252e-05 - mean_absolute_error: 0.0044 - val_loss: 7.6993e-05 - val_mean_absolute_error: 0.0065
Epoch 25/100
1/126 [..............................] - ETA: 0s - loss: 3.4955e-05 - mean_absolute_error: 0.0046 23/126 [====>.........................] - ETA: 0s - loss: 3.5921e-05 - mean_absolute_error: 0.0043 45/126 [=========>....................] - ETA: 0s - loss: 3.4727e-05 - mean_absolute_error: 0.0043 67/126 [==============>...............] - ETA: 0s - loss: 3.3658e-05 - mean_absolute_error: 0.0042 89/126 [====================>.........] - ETA: 0s - loss: 3.4886e-05 - mean_absolute_error: 0.0042109/126 [========================>.....] - ETA: 0s - loss: 3.5424e-05 - mean_absolute_error: 0.0043126/126 [==============================] - 0s 3ms/step - loss: 3.6305e-05 - mean_absolute_error: 0.0044 - val_loss: 6.9951e-05 - val_mean_absolute_error: 0.0060
Epoch 26/100
1/126 [..............................] - ETA: 0s - loss: 3.2173e-05 - mean_absolute_error: 0.0042 23/126 [====>.........................] - ETA: 0s - loss: 4.1872e-05 - mean_absolute_error: 0.0048 45/126 [=========>....................] - ETA: 0s - loss: 3.7437e-05 - mean_absolute_error: 0.0045 67/126 [==============>...............] - ETA: 0s - loss: 3.7366e-05 - mean_absolute_error: 0.0044 89/126 [====================>.........] - ETA: 0s - loss: 3.6788e-05 - mean_absolute_error: 0.0044110/126 [=========================>....] - ETA: 0s - loss: 3.6843e-05 - mean_absolute_error: 0.0044126/126 [==============================] - 0s 3ms/step - loss: 3.6956e-05 - mean_absolute_error: 0.0044 - val_loss: 8.8728e-05 - val_mean_absolute_error: 0.0073
Epoch 27/100
1/126 [..............................] - ETA: 0s - loss: 2.2952e-05 - mean_absolute_error: 0.0041 23/126 [====>.........................] - ETA: 0s - loss: 3.8445e-05 - mean_absolute_error: 0.0046 44/126 [=========>....................] - ETA: 0s - loss: 3.8552e-05 - mean_absolute_error: 0.0047 66/126 [==============>...............] - ETA: 0s - loss: 3.9706e-05 - mean_absolute_error: 0.0048 88/126 [===================>..........] - ETA: 0s - loss: 3.9001e-05 - mean_absolute_error: 0.0046110/126 [=========================>....] - ETA: 0s - loss: 3.8627e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 3.9460e-05 - mean_absolute_error: 0.0047 - val_loss: 7.4942e-05 - val_mean_absolute_error: 0.0064
Epoch 28/100
1/126 [..............................] - ETA: 0s - loss: 4.1784e-05 - mean_absolute_error: 0.0053 22/126 [====>.........................] - ETA: 0s - loss: 3.9650e-05 - mean_absolute_error: 0.0048 43/126 [=========>....................] - ETA: 0s - loss: 4.0687e-05 - mean_absolute_error: 0.0049 64/126 [==============>...............] - ETA: 0s - loss: 3.7917e-05 - mean_absolute_error: 0.0046 85/126 [===================>..........] - ETA: 0s - loss: 3.7136e-05 - mean_absolute_error: 0.0045107/126 [========================>.....] - ETA: 0s - loss: 3.7157e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.9273e-05 - mean_absolute_error: 0.0047 - val_loss: 1.0058e-04 - val_mean_absolute_error: 0.0080
Epoch 29/100
1/126 [..............................] - ETA: 0s - loss: 4.4650e-05 - mean_absolute_error: 0.0059 23/126 [====>.........................] - ETA: 0s - loss: 4.0660e-05 - mean_absolute_error: 0.0050 45/126 [=========>....................] - ETA: 0s - loss: 3.7474e-05 - mean_absolute_error: 0.0047 67/126 [==============>...............] - ETA: 0s - loss: 3.8921e-05 - mean_absolute_error: 0.0048 89/126 [====================>.........] - ETA: 0s - loss: 4.2678e-05 - mean_absolute_error: 0.0050110/126 [=========================>....] - ETA: 0s - loss: 4.0979e-05 - mean_absolute_error: 0.0048126/126 [==============================] - 0s 3ms/step - loss: 4.0878e-05 - mean_absolute_error: 0.0048 - val_loss: 8.2899e-05 - val_mean_absolute_error: 0.0070
Epoch 30/100
1/126 [..............................] - ETA: 0s - loss: 4.9858e-05 - mean_absolute_error: 0.0056 22/126 [====>.........................] - ETA: 0s - loss: 3.9391e-05 - mean_absolute_error: 0.0046 44/126 [=========>....................] - ETA: 0s - loss: 3.7968e-05 - mean_absolute_error: 0.0046 66/126 [==============>...............] - ETA: 0s - loss: 3.7613e-05 - mean_absolute_error: 0.0045 87/126 [===================>..........] - ETA: 0s - loss: 3.6655e-05 - mean_absolute_error: 0.0044108/126 [========================>.....] - ETA: 0s - loss: 3.6612e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.6692e-05 - mean_absolute_error: 0.0044 - val_loss: 6.6116e-05 - val_mean_absolute_error: 0.0057
Epoch 31/100
1/126 [..............................] - ETA: 0s - loss: 2.5106e-05 - mean_absolute_error: 0.0040 23/126 [====>.........................] - ETA: 0s - loss: 4.2141e-05 - mean_absolute_error: 0.0050 45/126 [=========>....................] - ETA: 0s - loss: 4.8111e-05 - mean_absolute_error: 0.0053 67/126 [==============>...............] - ETA: 0s - loss: 4.4957e-05 - mean_absolute_error: 0.0052 89/126 [====================>.........] - ETA: 0s - loss: 4.3724e-05 - mean_absolute_error: 0.0051111/126 [=========================>....] - ETA: 0s - loss: 4.1889e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.1003e-05 - mean_absolute_error: 0.0049 - val_loss: 6.5601e-05 - val_mean_absolute_error: 0.0054
Epoch 32/100
1/126 [..............................] - ETA: 0s - loss: 4.1853e-05 - mean_absolute_error: 0.0049 23/126 [====>.........................] - ETA: 0s - loss: 3.4908e-05 - mean_absolute_error: 0.0045 44/126 [=========>....................] - ETA: 0s - loss: 3.6809e-05 - mean_absolute_error: 0.0045 66/126 [==============>...............] - ETA: 0s - loss: 4.3604e-05 - mean_absolute_error: 0.0049 87/126 [===================>..........] - ETA: 0s - loss: 4.4356e-05 - mean_absolute_error: 0.0050108/126 [========================>.....] - ETA: 0s - loss: 4.2579e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.2760e-05 - mean_absolute_error: 0.0049 - val_loss: 7.8797e-05 - val_mean_absolute_error: 0.0067
Epoch 33/100
1/126 [..............................] - ETA: 0s - loss: 4.3986e-05 - mean_absolute_error: 0.0056 23/126 [====>.........................] - ETA: 0s - loss: 3.9043e-05 - mean_absolute_error: 0.0047 44/126 [=========>....................] - ETA: 0s - loss: 3.5329e-05 - mean_absolute_error: 0.0044 65/126 [==============>...............] - ETA: 0s - loss: 3.5577e-05 - mean_absolute_error: 0.0044 87/126 [===================>..........] - ETA: 0s - loss: 3.7664e-05 - mean_absolute_error: 0.0046109/126 [========================>.....] - ETA: 0s - loss: 4.1227e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.2306e-05 - mean_absolute_error: 0.0049 - val_loss: 9.1872e-05 - val_mean_absolute_error: 0.0076
Epoch 34/100
1/126 [..............................] - ETA: 0s - loss: 4.5838e-05 - mean_absolute_error: 0.0059 22/126 [====>.........................] - ETA: 0s - loss: 4.0660e-05 - mean_absolute_error: 0.0049 43/126 [=========>....................] - ETA: 0s - loss: 4.0671e-05 - mean_absolute_error: 0.0047 65/126 [==============>...............] - ETA: 0s - loss: 4.2550e-05 - mean_absolute_error: 0.0049 87/126 [===================>..........] - ETA: 0s - loss: 4.3019e-05 - mean_absolute_error: 0.0049108/126 [========================>.....] - ETA: 0s - loss: 4.2200e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.1515e-05 - mean_absolute_error: 0.0049 - val_loss: 6.9283e-05 - val_mean_absolute_error: 0.0059
Epoch 35/100
1/126 [..............................] - ETA: 0s - loss: 3.6824e-05 - mean_absolute_error: 0.0047 23/126 [====>.........................] - ETA: 0s - loss: 3.7121e-05 - mean_absolute_error: 0.0044 45/126 [=========>....................] - ETA: 0s - loss: 4.0605e-05 - mean_absolute_error: 0.0046 67/126 [==============>...............] - ETA: 0s - loss: 4.2966e-05 - mean_absolute_error: 0.0049 88/126 [===================>..........] - ETA: 0s - loss: 4.2407e-05 - mean_absolute_error: 0.0049109/126 [========================>.....] - ETA: 0s - loss: 4.1379e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.0327e-05 - mean_absolute_error: 0.0048 - val_loss: 7.0748e-05 - val_mean_absolute_error: 0.0061
Epoch 36/100
1/126 [..............................] - ETA: 0s - loss: 2.8060e-05 - mean_absolute_error: 0.0042 22/126 [====>.........................] - ETA: 0s - loss: 3.9227e-05 - mean_absolute_error: 0.0047 43/126 [=========>....................] - ETA: 0s - loss: 3.9521e-05 - mean_absolute_error: 0.0047 61/126 [=============>................] - ETA: 0s - loss: 3.7169e-05 - mean_absolute_error: 0.0045 79/126 [=================>............] - ETA: 0s - loss: 3.7275e-05 - mean_absolute_error: 0.0045 98/126 [======================>.......] - ETA: 0s - loss: 3.8108e-05 - mean_absolute_error: 0.0046118/126 [===========================>..] - ETA: 0s - loss: 3.8774e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 3.9703e-05 - mean_absolute_error: 0.0047 - val_loss: 8.4014e-05 - val_mean_absolute_error: 0.0071
Epoch 37/100
1/126 [..............................] - ETA: 0s - loss: 6.9098e-05 - mean_absolute_error: 0.0070 23/126 [====>.........................] - ETA: 0s - loss: 4.1441e-05 - mean_absolute_error: 0.0049 45/126 [=========>....................] - ETA: 0s - loss: 4.3907e-05 - mean_absolute_error: 0.0051 67/126 [==============>...............] - ETA: 0s - loss: 4.0161e-05 - mean_absolute_error: 0.0048 88/126 [===================>..........] - ETA: 0s - loss: 4.0019e-05 - mean_absolute_error: 0.0047109/126 [========================>.....] - ETA: 0s - loss: 4.2606e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.4263e-05 - mean_absolute_error: 0.0051 - val_loss: 6.7496e-05 - val_mean_absolute_error: 0.0057
Epoch 38/100
1/126 [..............................] - ETA: 0s - loss: 3.7014e-05 - mean_absolute_error: 0.0047 22/126 [====>.........................] - ETA: 0s - loss: 3.3126e-05 - mean_absolute_error: 0.0043 44/126 [=========>....................] - ETA: 0s - loss: 3.3923e-05 - mean_absolute_error: 0.0043 66/126 [==============>...............] - ETA: 0s - loss: 3.7453e-05 - mean_absolute_error: 0.0046 88/126 [===================>..........] - ETA: 0s - loss: 4.0758e-05 - mean_absolute_error: 0.0048109/126 [========================>.....] - ETA: 0s - loss: 4.2594e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.1633e-05 - mean_absolute_error: 0.0049 - val_loss: 7.1734e-05 - val_mean_absolute_error: 0.0060
Epoch 39/100
1/126 [..............................] - ETA: 0s - loss: 3.4761e-05 - mean_absolute_error: 0.0040 23/126 [====>.........................] - ETA: 0s - loss: 4.8619e-05 - mean_absolute_error: 0.0052 45/126 [=========>....................] - ETA: 0s - loss: 4.7527e-05 - mean_absolute_error: 0.0053 67/126 [==============>...............] - ETA: 0s - loss: 4.5168e-05 - mean_absolute_error: 0.0050 89/126 [====================>.........] - ETA: 0s - loss: 4.4497e-05 - mean_absolute_error: 0.0050111/126 [=========================>....] - ETA: 0s - loss: 4.2129e-05 - mean_absolute_error: 0.0048126/126 [==============================] - 0s 3ms/step - loss: 4.1422e-05 - mean_absolute_error: 0.0048 - val_loss: 6.6227e-05 - val_mean_absolute_error: 0.0055
Epoch 40/100
1/126 [..............................] - ETA: 0s - loss: 3.1369e-05 - mean_absolute_error: 0.0040 22/126 [====>.........................] - ETA: 0s - loss: 4.6384e-05 - mean_absolute_error: 0.0053 44/126 [=========>....................] - ETA: 0s - loss: 4.4199e-05 - mean_absolute_error: 0.0051 65/126 [==============>...............] - ETA: 0s - loss: 4.2093e-05 - mean_absolute_error: 0.0050 86/126 [===================>..........] - ETA: 0s - loss: 4.3423e-05 - mean_absolute_error: 0.0051107/126 [========================>.....] - ETA: 0s - loss: 4.3973e-05 - mean_absolute_error: 0.0051126/126 [==============================] - 0s 3ms/step - loss: 4.3396e-05 - mean_absolute_error: 0.0050 - val_loss: 7.7338e-05 - val_mean_absolute_error: 0.0066
Epoch 41/100
1/126 [..............................] - ETA: 0s - loss: 3.6557e-05 - mean_absolute_error: 0.0053 23/126 [====>.........................] - ETA: 0s - loss: 3.8099e-05 - mean_absolute_error: 0.0047 45/126 [=========>....................] - ETA: 0s - loss: 4.2248e-05 - mean_absolute_error: 0.0048 67/126 [==============>...............] - ETA: 0s - loss: 4.1240e-05 - mean_absolute_error: 0.0048 87/126 [===================>..........] - ETA: 0s - loss: 4.1518e-05 - mean_absolute_error: 0.0049108/126 [========================>.....] - ETA: 0s - loss: 3.9139e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 3.9803e-05 - mean_absolute_error: 0.0047 - val_loss: 1.2563e-04 - val_mean_absolute_error: 0.0088
Epoch 42/100
1/126 [..............................] - ETA: 0s - loss: 6.0113e-05 - mean_absolute_error: 0.0063 23/126 [====>.........................] - ETA: 0s - loss: 5.8257e-05 - mean_absolute_error: 0.0062 45/126 [=========>....................] - ETA: 0s - loss: 5.4055e-05 - mean_absolute_error: 0.0058 67/126 [==============>...............] - ETA: 0s - loss: 4.8773e-05 - mean_absolute_error: 0.0055 89/126 [====================>.........] - ETA: 0s - loss: 4.7192e-05 - mean_absolute_error: 0.0053110/126 [=========================>....] - ETA: 0s - loss: 4.5753e-05 - mean_absolute_error: 0.0052126/126 [==============================] - 0s 3ms/step - loss: 4.4544e-05 - mean_absolute_error: 0.0051 - val_loss: 6.5502e-05 - val_mean_absolute_error: 0.0055
Epoch 43/100
1/126 [..............................] - ETA: 0s - loss: 2.3661e-05 - mean_absolute_error: 0.0031 23/126 [====>.........................] - ETA: 0s - loss: 3.3763e-05 - mean_absolute_error: 0.0045 45/126 [=========>....................] - ETA: 0s - loss: 4.1685e-05 - mean_absolute_error: 0.0050 67/126 [==============>...............] - ETA: 0s - loss: 4.2818e-05 - mean_absolute_error: 0.0051 89/126 [====================>.........] - ETA: 0s - loss: 4.2088e-05 - mean_absolute_error: 0.0049109/126 [========================>.....] - ETA: 0s - loss: 4.0531e-05 - mean_absolute_error: 0.0048126/126 [==============================] - 0s 3ms/step - loss: 4.0436e-05 - mean_absolute_error: 0.0048 - val_loss: 6.8631e-05 - val_mean_absolute_error: 0.0060
Epoch 44/100
1/126 [..............................] - ETA: 0s - loss: 2.5348e-05 - mean_absolute_error: 0.0039 22/126 [====>.........................] - ETA: 0s - loss: 4.0431e-05 - mean_absolute_error: 0.0048 44/126 [=========>....................] - ETA: 0s - loss: 4.0064e-05 - mean_absolute_error: 0.0047 66/126 [==============>...............] - ETA: 0s - loss: 3.8512e-05 - mean_absolute_error: 0.0046 88/126 [===================>..........] - ETA: 0s - loss: 3.9369e-05 - mean_absolute_error: 0.0047109/126 [========================>.....] - ETA: 0s - loss: 4.0596e-05 - mean_absolute_error: 0.0048126/126 [==============================] - 0s 3ms/step - loss: 4.0576e-05 - mean_absolute_error: 0.0048 - val_loss: 1.4560e-04 - val_mean_absolute_error: 0.0098
Epoch 45/100
1/126 [..............................] - ETA: 0s - loss: 7.1391e-05 - mean_absolute_error: 0.0071 22/126 [====>.........................] - ETA: 0s - loss: 5.1454e-05 - mean_absolute_error: 0.0058 44/126 [=========>....................] - ETA: 0s - loss: 4.6579e-05 - mean_absolute_error: 0.0054 66/126 [==============>...............] - ETA: 0s - loss: 4.5179e-05 - mean_absolute_error: 0.0052 88/126 [===================>..........] - ETA: 0s - loss: 4.4065e-05 - mean_absolute_error: 0.0051109/126 [========================>.....] - ETA: 0s - loss: 4.3857e-05 - mean_absolute_error: 0.0051126/126 [==============================] - 0s 3ms/step - loss: 4.4143e-05 - mean_absolute_error: 0.0051 - val_loss: 8.6550e-05 - val_mean_absolute_error: 0.0069
Epoch 46/100
1/126 [..............................] - ETA: 0s - loss: 8.8423e-05 - mean_absolute_error: 0.0063 20/126 [===>..........................] - ETA: 0s - loss: 4.0356e-05 - mean_absolute_error: 0.0048 39/126 [========>.....................] - ETA: 0s - loss: 3.5969e-05 - mean_absolute_error: 0.0045 61/126 [=============>................] - ETA: 0s - loss: 3.6956e-05 - mean_absolute_error: 0.0046 81/126 [==================>...........] - ETA: 0s - loss: 4.1720e-05 - mean_absolute_error: 0.0049102/126 [=======================>......] - ETA: 0s - loss: 4.1184e-05 - mean_absolute_error: 0.0048123/126 [============================>.] - ETA: 0s - loss: 3.9837e-05 - mean_absolute_error: 0.0048126/126 [==============================] - 0s 3ms/step - loss: 4.0266e-05 - mean_absolute_error: 0.0048 - val_loss: 8.6748e-05 - val_mean_absolute_error: 0.0073
Epoch 47/100
1/126 [..............................] - ETA: 0s - loss: 3.2821e-05 - mean_absolute_error: 0.0046 22/126 [====>.........................] - ETA: 0s - loss: 4.5927e-05 - mean_absolute_error: 0.0053 43/126 [=========>....................] - ETA: 0s - loss: 4.1802e-05 - mean_absolute_error: 0.0050 64/126 [==============>...............] - ETA: 0s - loss: 4.0551e-05 - mean_absolute_error: 0.0048 85/126 [===================>..........] - ETA: 0s - loss: 3.9775e-05 - mean_absolute_error: 0.0048107/126 [========================>.....] - ETA: 0s - loss: 4.1516e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.0419e-05 - mean_absolute_error: 0.0048 - val_loss: 8.5289e-05 - val_mean_absolute_error: 0.0072
Epoch 48/100
1/126 [..............................] - ETA: 0s - loss: 4.5403e-05 - mean_absolute_error: 0.0055 23/126 [====>.........................] - ETA: 0s - loss: 5.4179e-05 - mean_absolute_error: 0.0058 45/126 [=========>....................] - ETA: 0s - loss: 5.1919e-05 - mean_absolute_error: 0.0056 66/126 [==============>...............] - ETA: 0s - loss: 4.8413e-05 - mean_absolute_error: 0.0054 86/126 [===================>..........] - ETA: 0s - loss: 4.4614e-05 - mean_absolute_error: 0.0051107/126 [========================>.....] - ETA: 0s - loss: 4.2697e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.2145e-05 - mean_absolute_error: 0.0049 - val_loss: 6.6828e-05 - val_mean_absolute_error: 0.0058
Epoch 49/100
1/126 [..............................] - ETA: 0s - loss: 1.6543e-05 - mean_absolute_error: 0.0027 23/126 [====>.........................] - ETA: 0s - loss: 4.1931e-05 - mean_absolute_error: 0.0050 45/126 [=========>....................] - ETA: 0s - loss: 4.1976e-05 - mean_absolute_error: 0.0050 67/126 [==============>...............] - ETA: 0s - loss: 3.9664e-05 - mean_absolute_error: 0.0048 89/126 [====================>.........] - ETA: 0s - loss: 3.9224e-05 - mean_absolute_error: 0.0047111/126 [=========================>....] - ETA: 0s - loss: 3.9119e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 3.8825e-05 - mean_absolute_error: 0.0046 - val_loss: 6.6686e-05 - val_mean_absolute_error: 0.0057
Epoch 50/100
1/126 [..............................] - ETA: 0s - loss: 2.9896e-05 - mean_absolute_error: 0.0043 23/126 [====>.........................] - ETA: 0s - loss: 4.2487e-05 - mean_absolute_error: 0.0049 45/126 [=========>....................] - ETA: 0s - loss: 3.7656e-05 - mean_absolute_error: 0.0046 67/126 [==============>...............] - ETA: 0s - loss: 3.6905e-05 - mean_absolute_error: 0.0046 89/126 [====================>.........] - ETA: 0s - loss: 3.6719e-05 - mean_absolute_error: 0.0045111/126 [=========================>....] - ETA: 0s - loss: 3.7652e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 3.7963e-05 - mean_absolute_error: 0.0046 - val_loss: 6.5895e-05 - val_mean_absolute_error: 0.0056
Epoch 51/100
1/126 [..............................] - ETA: 0s - loss: 2.4016e-05 - mean_absolute_error: 0.0037 23/126 [====>.........................] - ETA: 0s - loss: 3.8351e-05 - mean_absolute_error: 0.0045 45/126 [=========>....................] - ETA: 0s - loss: 3.7819e-05 - mean_absolute_error: 0.0045 67/126 [==============>...............] - ETA: 0s - loss: 3.8688e-05 - mean_absolute_error: 0.0046 88/126 [===================>..........] - ETA: 0s - loss: 3.8933e-05 - mean_absolute_error: 0.0047109/126 [========================>.....] - ETA: 0s - loss: 4.1137e-05 - mean_absolute_error: 0.0048126/126 [==============================] - 0s 3ms/step - loss: 4.1108e-05 - mean_absolute_error: 0.0048 - val_loss: 8.3339e-05 - val_mean_absolute_error: 0.0068
Epoch 52/100
1/126 [..............................] - ETA: 0s - loss: 4.8679e-05 - mean_absolute_error: 0.0059 23/126 [====>.........................] - ETA: 0s - loss: 4.4062e-05 - mean_absolute_error: 0.0051 45/126 [=========>....................] - ETA: 0s - loss: 3.9841e-05 - mean_absolute_error: 0.0048 67/126 [==============>...............] - ETA: 0s - loss: 3.8711e-05 - mean_absolute_error: 0.0047 89/126 [====================>.........] - ETA: 0s - loss: 4.0704e-05 - mean_absolute_error: 0.0048111/126 [=========================>....] - ETA: 0s - loss: 4.3608e-05 - mean_absolute_error: 0.0050126/126 [==============================] - 0s 3ms/step - loss: 4.2854e-05 - mean_absolute_error: 0.0050 - val_loss: 6.5047e-05 - val_mean_absolute_error: 0.0057
Epoch 53/100
1/126 [..............................] - ETA: 0s - loss: 1.6351e-05 - mean_absolute_error: 0.0029 21/126 [====>.........................] - ETA: 0s - loss: 4.7275e-05 - mean_absolute_error: 0.0052 43/126 [=========>....................] - ETA: 0s - loss: 4.8114e-05 - mean_absolute_error: 0.0053 65/126 [==============>...............] - ETA: 0s - loss: 4.4078e-05 - mean_absolute_error: 0.0050 86/126 [===================>..........] - ETA: 0s - loss: 4.3894e-05 - mean_absolute_error: 0.0050107/126 [========================>.....] - ETA: 0s - loss: 4.1925e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.0201e-05 - mean_absolute_error: 0.0047 - val_loss: 6.4247e-05 - val_mean_absolute_error: 0.0054
Epoch 54/100
1/126 [..............................] - ETA: 0s - loss: 5.5913e-05 - mean_absolute_error: 0.0046 22/126 [====>.........................] - ETA: 0s - loss: 3.5682e-05 - mean_absolute_error: 0.0043 43/126 [=========>....................] - ETA: 0s - loss: 3.8080e-05 - mean_absolute_error: 0.0047 64/126 [==============>...............] - ETA: 0s - loss: 4.1649e-05 - mean_absolute_error: 0.0049 84/126 [===================>..........] - ETA: 0s - loss: 4.5702e-05 - mean_absolute_error: 0.0052105/126 [========================>.....] - ETA: 0s - loss: 4.4743e-05 - mean_absolute_error: 0.0051126/126 [==============================] - ETA: 0s - loss: 4.2978e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.2978e-05 - mean_absolute_error: 0.0049 - val_loss: 6.8094e-05 - val_mean_absolute_error: 0.0058
Epoch 55/100
1/126 [..............................] - ETA: 0s - loss: 3.4636e-05 - mean_absolute_error: 0.0045 23/126 [====>.........................] - ETA: 0s - loss: 4.1000e-05 - mean_absolute_error: 0.0047 45/126 [=========>....................] - ETA: 0s - loss: 3.7816e-05 - mean_absolute_error: 0.0045 67/126 [==============>...............] - ETA: 0s - loss: 3.6691e-05 - mean_absolute_error: 0.0044 89/126 [====================>.........] - ETA: 0s - loss: 3.5875e-05 - mean_absolute_error: 0.0044110/126 [=========================>....] - ETA: 0s - loss: 3.7406e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.7899e-05 - mean_absolute_error: 0.0046 - val_loss: 7.8153e-05 - val_mean_absolute_error: 0.0065
Epoch 56/100
1/126 [..............................] - ETA: 0s - loss: 2.6326e-05 - mean_absolute_error: 0.0041 22/126 [====>.........................] - ETA: 0s - loss: 3.1987e-05 - mean_absolute_error: 0.0042 43/126 [=========>....................] - ETA: 0s - loss: 3.5621e-05 - mean_absolute_error: 0.0045 65/126 [==============>...............] - ETA: 0s - loss: 3.7881e-05 - mean_absolute_error: 0.0047 86/126 [===================>..........] - ETA: 0s - loss: 3.7183e-05 - mean_absolute_error: 0.0046106/126 [========================>.....] - ETA: 0s - loss: 3.6236e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.6864e-05 - mean_absolute_error: 0.0046 - val_loss: 8.0206e-05 - val_mean_absolute_error: 0.0066
Epoch 57/100
1/126 [..............................] - ETA: 0s - loss: 4.6483e-05 - mean_absolute_error: 0.0050 22/126 [====>.........................] - ETA: 0s - loss: 4.7895e-05 - mean_absolute_error: 0.0052 43/126 [=========>....................] - ETA: 0s - loss: 4.2909e-05 - mean_absolute_error: 0.0049 64/126 [==============>...............] - ETA: 0s - loss: 4.8029e-05 - mean_absolute_error: 0.0053 86/126 [===================>..........] - ETA: 0s - loss: 5.1904e-05 - mean_absolute_error: 0.0056106/126 [========================>.....] - ETA: 0s - loss: 4.9449e-05 - mean_absolute_error: 0.0055126/126 [==============================] - 0s 3ms/step - loss: 4.7747e-05 - mean_absolute_error: 0.0053 - val_loss: 6.4395e-05 - val_mean_absolute_error: 0.0055
Epoch 58/100
1/126 [..............................] - ETA: 0s - loss: 2.1579e-05 - mean_absolute_error: 0.0031 23/126 [====>.........................] - ETA: 0s - loss: 3.7707e-05 - mean_absolute_error: 0.0047 45/126 [=========>....................] - ETA: 0s - loss: 3.6983e-05 - mean_absolute_error: 0.0046 67/126 [==============>...............] - ETA: 0s - loss: 3.5865e-05 - mean_absolute_error: 0.0045 89/126 [====================>.........] - ETA: 0s - loss: 3.6587e-05 - mean_absolute_error: 0.0045111/126 [=========================>....] - ETA: 0s - loss: 3.7029e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.6601e-05 - mean_absolute_error: 0.0045 - val_loss: 6.5400e-05 - val_mean_absolute_error: 0.0056
Epoch 59/100
1/126 [..............................] - ETA: 0s - loss: 4.7583e-05 - mean_absolute_error: 0.0051 23/126 [====>.........................] - ETA: 0s - loss: 3.6661e-05 - mean_absolute_error: 0.0045 45/126 [=========>....................] - ETA: 0s - loss: 3.7026e-05 - mean_absolute_error: 0.0043 67/126 [==============>...............] - ETA: 0s - loss: 3.9628e-05 - mean_absolute_error: 0.0047 88/126 [===================>..........] - ETA: 0s - loss: 4.0384e-05 - mean_absolute_error: 0.0048109/126 [========================>.....] - ETA: 0s - loss: 3.9544e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 4.0103e-05 - mean_absolute_error: 0.0048 - val_loss: 9.5409e-05 - val_mean_absolute_error: 0.0075
Epoch 60/100
1/126 [..............................] - ETA: 0s - loss: 3.7714e-05 - mean_absolute_error: 0.0053 23/126 [====>.........................] - ETA: 0s - loss: 5.6508e-05 - mean_absolute_error: 0.0061 45/126 [=========>....................] - ETA: 0s - loss: 6.1940e-05 - mean_absolute_error: 0.0063 67/126 [==============>...............] - ETA: 0s - loss: 5.4517e-05 - mean_absolute_error: 0.0058 88/126 [===================>..........] - ETA: 0s - loss: 5.3224e-05 - mean_absolute_error: 0.0057110/126 [=========================>....] - ETA: 0s - loss: 4.8443e-05 - mean_absolute_error: 0.0054126/126 [==============================] - 0s 3ms/step - loss: 4.6820e-05 - mean_absolute_error: 0.0053 - val_loss: 9.0087e-05 - val_mean_absolute_error: 0.0072
Epoch 61/100
1/126 [..............................] - ETA: 0s - loss: 3.6837e-05 - mean_absolute_error: 0.0053 23/126 [====>.........................] - ETA: 0s - loss: 4.4031e-05 - mean_absolute_error: 0.0050 44/126 [=========>....................] - ETA: 0s - loss: 4.5504e-05 - mean_absolute_error: 0.0052 66/126 [==============>...............] - ETA: 0s - loss: 4.1444e-05 - mean_absolute_error: 0.0048 88/126 [===================>..........] - ETA: 0s - loss: 4.2508e-05 - mean_absolute_error: 0.0049110/126 [=========================>....] - ETA: 0s - loss: 4.1330e-05 - mean_absolute_error: 0.0048126/126 [==============================] - 0s 3ms/step - loss: 4.1326e-05 - mean_absolute_error: 0.0048 - val_loss: 8.1730e-05 - val_mean_absolute_error: 0.0070
Epoch 62/100
1/126 [..............................] - ETA: 0s - loss: 2.9870e-05 - mean_absolute_error: 0.0043 23/126 [====>.........................] - ETA: 0s - loss: 3.6876e-05 - mean_absolute_error: 0.0046 45/126 [=========>....................] - ETA: 0s - loss: 4.3135e-05 - mean_absolute_error: 0.0051 67/126 [==============>...............] - ETA: 0s - loss: 4.3335e-05 - mean_absolute_error: 0.0050 88/126 [===================>..........] - ETA: 0s - loss: 4.2362e-05 - mean_absolute_error: 0.0050109/126 [========================>.....] - ETA: 0s - loss: 4.1520e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.1399e-05 - mean_absolute_error: 0.0049 - val_loss: 7.4635e-05 - val_mean_absolute_error: 0.0063
Epoch 63/100
1/126 [..............................] - ETA: 0s - loss: 3.0923e-05 - mean_absolute_error: 0.0044 23/126 [====>.........................] - ETA: 0s - loss: 3.3626e-05 - mean_absolute_error: 0.0042 45/126 [=========>....................] - ETA: 0s - loss: 3.6705e-05 - mean_absolute_error: 0.0044 67/126 [==============>...............] - ETA: 0s - loss: 3.5107e-05 - mean_absolute_error: 0.0044 88/126 [===================>..........] - ETA: 0s - loss: 3.5143e-05 - mean_absolute_error: 0.0044109/126 [========================>.....] - ETA: 0s - loss: 3.5878e-05 - mean_absolute_error: 0.0044126/126 [==============================] - 0s 3ms/step - loss: 3.7995e-05 - mean_absolute_error: 0.0045 - val_loss: 7.7299e-05 - val_mean_absolute_error: 0.0064
Epoch 64/100
1/126 [..............................] - ETA: 0s - loss: 9.4389e-05 - mean_absolute_error: 0.0068 23/126 [====>.........................] - ETA: 0s - loss: 4.4925e-05 - mean_absolute_error: 0.0050 44/126 [=========>....................] - ETA: 0s - loss: 4.1947e-05 - mean_absolute_error: 0.0049 66/126 [==============>...............] - ETA: 0s - loss: 3.8291e-05 - mean_absolute_error: 0.0046 87/126 [===================>..........] - ETA: 0s - loss: 3.7031e-05 - mean_absolute_error: 0.0045108/126 [========================>.....] - ETA: 0s - loss: 3.8400e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 4.0641e-05 - mean_absolute_error: 0.0047 - val_loss: 6.3130e-05 - val_mean_absolute_error: 0.0054
Epoch 65/100
1/126 [..............................] - ETA: 0s - loss: 3.7011e-05 - mean_absolute_error: 0.0034 22/126 [====>.........................] - ETA: 0s - loss: 3.4982e-05 - mean_absolute_error: 0.0044 43/126 [=========>....................] - ETA: 0s - loss: 3.9341e-05 - mean_absolute_error: 0.0047 64/126 [==============>...............] - ETA: 0s - loss: 4.0610e-05 - mean_absolute_error: 0.0048 85/126 [===================>..........] - ETA: 0s - loss: 3.8065e-05 - mean_absolute_error: 0.0046106/126 [========================>.....] - ETA: 0s - loss: 3.7021e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.8185e-05 - mean_absolute_error: 0.0046 - val_loss: 7.9553e-05 - val_mean_absolute_error: 0.0069
Epoch 66/100
1/126 [..............................] - ETA: 0s - loss: 4.0124e-05 - mean_absolute_error: 0.0051 23/126 [====>.........................] - ETA: 0s - loss: 4.2229e-05 - mean_absolute_error: 0.0049 43/126 [=========>....................] - ETA: 0s - loss: 3.9562e-05 - mean_absolute_error: 0.0047 63/126 [==============>...............] - ETA: 0s - loss: 3.9377e-05 - mean_absolute_error: 0.0047 84/126 [===================>..........] - ETA: 0s - loss: 4.6388e-05 - mean_absolute_error: 0.0052105/126 [========================>.....] - ETA: 0s - loss: 4.5431e-05 - mean_absolute_error: 0.0051126/126 [==============================] - 0s 3ms/step - loss: 4.3307e-05 - mean_absolute_error: 0.0050 - val_loss: 6.8921e-05 - val_mean_absolute_error: 0.0061
Epoch 67/100
1/126 [..............................] - ETA: 0s - loss: 1.9079e-05 - mean_absolute_error: 0.0038 23/126 [====>.........................] - ETA: 0s - loss: 3.0139e-05 - mean_absolute_error: 0.0042 45/126 [=========>....................] - ETA: 0s - loss: 3.8054e-05 - mean_absolute_error: 0.0047 67/126 [==============>...............] - ETA: 0s - loss: 4.4177e-05 - mean_absolute_error: 0.0052 89/126 [====================>.........] - ETA: 0s - loss: 4.7792e-05 - mean_absolute_error: 0.0054110/126 [=========================>....] - ETA: 0s - loss: 4.6024e-05 - mean_absolute_error: 0.0052126/126 [==============================] - 0s 3ms/step - loss: 4.3727e-05 - mean_absolute_error: 0.0051 - val_loss: 6.5962e-05 - val_mean_absolute_error: 0.0057
Epoch 68/100
1/126 [..............................] - ETA: 0s - loss: 4.8046e-05 - mean_absolute_error: 0.0053 23/126 [====>.........................] - ETA: 0s - loss: 4.0184e-05 - mean_absolute_error: 0.0048 45/126 [=========>....................] - ETA: 0s - loss: 3.8854e-05 - mean_absolute_error: 0.0047 67/126 [==============>...............] - ETA: 0s - loss: 3.8336e-05 - mean_absolute_error: 0.0047 88/126 [===================>..........] - ETA: 0s - loss: 4.4468e-05 - mean_absolute_error: 0.0051109/126 [========================>.....] - ETA: 0s - loss: 4.4396e-05 - mean_absolute_error: 0.0051126/126 [==============================] - 0s 3ms/step - loss: 4.5106e-05 - mean_absolute_error: 0.0052 - val_loss: 7.7957e-05 - val_mean_absolute_error: 0.0065
Epoch 69/100
1/126 [..............................] - ETA: 0s - loss: 4.4028e-05 - mean_absolute_error: 0.0050 22/126 [====>.........................] - ETA: 0s - loss: 3.5021e-05 - mean_absolute_error: 0.0045 43/126 [=========>....................] - ETA: 0s - loss: 3.4650e-05 - mean_absolute_error: 0.0044 64/126 [==============>...............] - ETA: 0s - loss: 3.4567e-05 - mean_absolute_error: 0.0045 85/126 [===================>..........] - ETA: 0s - loss: 3.5785e-05 - mean_absolute_error: 0.0045106/126 [========================>.....] - ETA: 0s - loss: 3.7826e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 4.1607e-05 - mean_absolute_error: 0.0049 - val_loss: 1.0551e-04 - val_mean_absolute_error: 0.0084
Epoch 70/100
1/126 [..............................] - ETA: 0s - loss: 7.0744e-05 - mean_absolute_error: 0.0071 23/126 [====>.........................] - ETA: 0s - loss: 5.3026e-05 - mean_absolute_error: 0.0056 45/126 [=========>....................] - ETA: 0s - loss: 4.1976e-05 - mean_absolute_error: 0.0048 66/126 [==============>...............] - ETA: 0s - loss: 3.9655e-05 - mean_absolute_error: 0.0047 87/126 [===================>..........] - ETA: 0s - loss: 3.9447e-05 - mean_absolute_error: 0.0047108/126 [========================>.....] - ETA: 0s - loss: 4.1971e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.1268e-05 - mean_absolute_error: 0.0048 - val_loss: 8.7992e-05 - val_mean_absolute_error: 0.0074
Epoch 71/100
1/126 [..............................] - ETA: 0s - loss: 4.4708e-05 - mean_absolute_error: 0.0054 23/126 [====>.........................] - ETA: 0s - loss: 5.1773e-05 - mean_absolute_error: 0.0056 45/126 [=========>....................] - ETA: 0s - loss: 5.2634e-05 - mean_absolute_error: 0.0057 67/126 [==============>...............] - ETA: 0s - loss: 4.8088e-05 - mean_absolute_error: 0.0054 88/126 [===================>..........] - ETA: 0s - loss: 4.5858e-05 - mean_absolute_error: 0.0052109/126 [========================>.....] - ETA: 0s - loss: 4.2723e-05 - mean_absolute_error: 0.0050126/126 [==============================] - 0s 3ms/step - loss: 4.2064e-05 - mean_absolute_error: 0.0049 - val_loss: 7.4003e-05 - val_mean_absolute_error: 0.0063
Epoch 72/100
1/126 [..............................] - ETA: 0s - loss: 3.4978e-05 - mean_absolute_error: 0.0048 22/126 [====>.........................] - ETA: 0s - loss: 4.0439e-05 - mean_absolute_error: 0.0048 44/126 [=========>....................] - ETA: 0s - loss: 3.6055e-05 - mean_absolute_error: 0.0044 66/126 [==============>...............] - ETA: 0s - loss: 4.0598e-05 - mean_absolute_error: 0.0048 88/126 [===================>..........] - ETA: 0s - loss: 3.8459e-05 - mean_absolute_error: 0.0046109/126 [========================>.....] - ETA: 0s - loss: 3.8288e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 3.8008e-05 - mean_absolute_error: 0.0046 - val_loss: 7.4252e-05 - val_mean_absolute_error: 0.0063
Epoch 73/100
1/126 [..............................] - ETA: 0s - loss: 5.9839e-05 - mean_absolute_error: 0.0059 23/126 [====>.........................] - ETA: 0s - loss: 4.4423e-05 - mean_absolute_error: 0.0049 44/126 [=========>....................] - ETA: 0s - loss: 3.9914e-05 - mean_absolute_error: 0.0048 66/126 [==============>...............] - ETA: 0s - loss: 3.8115e-05 - mean_absolute_error: 0.0047 88/126 [===================>..........] - ETA: 0s - loss: 3.8787e-05 - mean_absolute_error: 0.0047110/126 [=========================>....] - ETA: 0s - loss: 3.8391e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 3.8262e-05 - mean_absolute_error: 0.0047 - val_loss: 6.2586e-05 - val_mean_absolute_error: 0.0055
Epoch 74/100
1/126 [..............................] - ETA: 0s - loss: 1.7452e-05 - mean_absolute_error: 0.0029 22/126 [====>.........................] - ETA: 0s - loss: 3.3387e-05 - mean_absolute_error: 0.0043 44/126 [=========>....................] - ETA: 0s - loss: 3.4198e-05 - mean_absolute_error: 0.0044 65/126 [==============>...............] - ETA: 0s - loss: 3.5340e-05 - mean_absolute_error: 0.0044 87/126 [===================>..........] - ETA: 0s - loss: 3.4386e-05 - mean_absolute_error: 0.0043108/126 [========================>.....] - ETA: 0s - loss: 3.4531e-05 - mean_absolute_error: 0.0043126/126 [==============================] - 0s 3ms/step - loss: 3.4766e-05 - mean_absolute_error: 0.0043 - val_loss: 6.0939e-05 - val_mean_absolute_error: 0.0053
Epoch 75/100
1/126 [..............................] - ETA: 0s - loss: 4.2114e-05 - mean_absolute_error: 0.0047 22/126 [====>.........................] - ETA: 0s - loss: 3.9487e-05 - mean_absolute_error: 0.0049 44/126 [=========>....................] - ETA: 0s - loss: 3.6451e-05 - mean_absolute_error: 0.0047 65/126 [==============>...............] - ETA: 0s - loss: 3.7545e-05 - mean_absolute_error: 0.0047 86/126 [===================>..........] - ETA: 0s - loss: 3.8069e-05 - mean_absolute_error: 0.0047107/126 [========================>.....] - ETA: 0s - loss: 4.0897e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 3.9692e-05 - mean_absolute_error: 0.0048 - val_loss: 6.1380e-05 - val_mean_absolute_error: 0.0053
Epoch 76/100
1/126 [..............................] - ETA: 0s - loss: 3.8021e-05 - mean_absolute_error: 0.0044 22/126 [====>.........................] - ETA: 0s - loss: 3.4564e-05 - mean_absolute_error: 0.0045 43/126 [=========>....................] - ETA: 0s - loss: 3.4714e-05 - mean_absolute_error: 0.0043 64/126 [==============>...............] - ETA: 0s - loss: 3.4429e-05 - mean_absolute_error: 0.0043 86/126 [===================>..........] - ETA: 0s - loss: 3.4136e-05 - mean_absolute_error: 0.0043108/126 [========================>.....] - ETA: 0s - loss: 3.5051e-05 - mean_absolute_error: 0.0043126/126 [==============================] - 0s 3ms/step - loss: 3.5111e-05 - mean_absolute_error: 0.0043 - val_loss: 6.1023e-05 - val_mean_absolute_error: 0.0053
Epoch 77/100
1/126 [..............................] - ETA: 0s - loss: 3.1327e-05 - mean_absolute_error: 0.0038 23/126 [====>.........................] - ETA: 0s - loss: 3.5810e-05 - mean_absolute_error: 0.0044 45/126 [=========>....................] - ETA: 0s - loss: 3.7781e-05 - mean_absolute_error: 0.0045 67/126 [==============>...............] - ETA: 0s - loss: 3.8535e-05 - mean_absolute_error: 0.0046 89/126 [====================>.........] - ETA: 0s - loss: 3.8911e-05 - mean_absolute_error: 0.0047110/126 [=========================>....] - ETA: 0s - loss: 3.8241e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 3.7473e-05 - mean_absolute_error: 0.0046 - val_loss: 6.8495e-05 - val_mean_absolute_error: 0.0059
Epoch 78/100
1/126 [..............................] - ETA: 0s - loss: 3.0289e-05 - mean_absolute_error: 0.0045 23/126 [====>.........................] - ETA: 0s - loss: 3.1801e-05 - mean_absolute_error: 0.0043 45/126 [=========>....................] - ETA: 0s - loss: 3.5698e-05 - mean_absolute_error: 0.0044 67/126 [==============>...............] - ETA: 0s - loss: 3.4996e-05 - mean_absolute_error: 0.0043 89/126 [====================>.........] - ETA: 0s - loss: 3.7444e-05 - mean_absolute_error: 0.0045111/126 [=========================>....] - ETA: 0s - loss: 4.0314e-05 - mean_absolute_error: 0.0048126/126 [==============================] - 0s 3ms/step - loss: 3.9848e-05 - mean_absolute_error: 0.0047 - val_loss: 9.9171e-05 - val_mean_absolute_error: 0.0077
Epoch 79/100
1/126 [..............................] - ETA: 0s - loss: 5.7980e-05 - mean_absolute_error: 0.0066 23/126 [====>.........................] - ETA: 0s - loss: 3.9074e-05 - mean_absolute_error: 0.0048 45/126 [=========>....................] - ETA: 0s - loss: 3.7200e-05 - mean_absolute_error: 0.0046 67/126 [==============>...............] - ETA: 0s - loss: 3.8888e-05 - mean_absolute_error: 0.0047 89/126 [====================>.........] - ETA: 0s - loss: 3.9018e-05 - mean_absolute_error: 0.0048111/126 [=========================>....] - ETA: 0s - loss: 4.1473e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.0528e-05 - mean_absolute_error: 0.0048 - val_loss: 6.0721e-05 - val_mean_absolute_error: 0.0053
Epoch 80/100
1/126 [..............................] - ETA: 0s - loss: 3.4129e-05 - mean_absolute_error: 0.0040 23/126 [====>.........................] - ETA: 0s - loss: 3.8829e-05 - mean_absolute_error: 0.0046 45/126 [=========>....................] - ETA: 0s - loss: 4.3220e-05 - mean_absolute_error: 0.0050 66/126 [==============>...............] - ETA: 0s - loss: 4.2228e-05 - mean_absolute_error: 0.0049 88/126 [===================>..........] - ETA: 0s - loss: 4.2452e-05 - mean_absolute_error: 0.0050109/126 [========================>.....] - ETA: 0s - loss: 4.2993e-05 - mean_absolute_error: 0.0050126/126 [==============================] - 0s 3ms/step - loss: 4.2651e-05 - mean_absolute_error: 0.0050 - val_loss: 8.3948e-05 - val_mean_absolute_error: 0.0072
Epoch 81/100
1/126 [..............................] - ETA: 0s - loss: 5.8735e-05 - mean_absolute_error: 0.0063 23/126 [====>.........................] - ETA: 0s - loss: 3.4979e-05 - mean_absolute_error: 0.0043 45/126 [=========>....................] - ETA: 0s - loss: 3.8628e-05 - mean_absolute_error: 0.0046 67/126 [==============>...............] - ETA: 0s - loss: 3.6855e-05 - mean_absolute_error: 0.0045 89/126 [====================>.........] - ETA: 0s - loss: 3.5408e-05 - mean_absolute_error: 0.0044110/126 [=========================>....] - ETA: 0s - loss: 3.5151e-05 - mean_absolute_error: 0.0043126/126 [==============================] - 0s 3ms/step - loss: 3.5429e-05 - mean_absolute_error: 0.0044 - val_loss: 7.3773e-05 - val_mean_absolute_error: 0.0063
Epoch 82/100
1/126 [..............................] - ETA: 0s - loss: 4.3450e-05 - mean_absolute_error: 0.0053 23/126 [====>.........................] - ETA: 0s - loss: 3.0248e-05 - mean_absolute_error: 0.0041 45/126 [=========>....................] - ETA: 0s - loss: 3.3540e-05 - mean_absolute_error: 0.0042 67/126 [==============>...............] - ETA: 0s - loss: 3.4256e-05 - mean_absolute_error: 0.0043 88/126 [===================>..........] - ETA: 0s - loss: 3.7283e-05 - mean_absolute_error: 0.0045109/126 [========================>.....] - ETA: 0s - loss: 3.9047e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 3.8584e-05 - mean_absolute_error: 0.0046 - val_loss: 1.2357e-04 - val_mean_absolute_error: 0.0089
Epoch 83/100
1/126 [..............................] - ETA: 0s - loss: 8.4060e-05 - mean_absolute_error: 0.0078 23/126 [====>.........................] - ETA: 0s - loss: 4.6132e-05 - mean_absolute_error: 0.0051 45/126 [=========>....................] - ETA: 0s - loss: 4.0428e-05 - mean_absolute_error: 0.0046 67/126 [==============>...............] - ETA: 0s - loss: 3.7143e-05 - mean_absolute_error: 0.0045 88/126 [===================>..........] - ETA: 0s - loss: 3.7988e-05 - mean_absolute_error: 0.0045109/126 [========================>.....] - ETA: 0s - loss: 3.9565e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 3.8616e-05 - mean_absolute_error: 0.0046 - val_loss: 6.9125e-05 - val_mean_absolute_error: 0.0062
Epoch 84/100
1/126 [..............................] - ETA: 0s - loss: 5.6275e-05 - mean_absolute_error: 0.0055 23/126 [====>.........................] - ETA: 0s - loss: 4.5314e-05 - mean_absolute_error: 0.0051 45/126 [=========>....................] - ETA: 0s - loss: 4.5060e-05 - mean_absolute_error: 0.0051 67/126 [==============>...............] - ETA: 0s - loss: 4.4052e-05 - mean_absolute_error: 0.0051 89/126 [====================>.........] - ETA: 0s - loss: 4.0357e-05 - mean_absolute_error: 0.0048111/126 [=========================>....] - ETA: 0s - loss: 3.9277e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 3.8291e-05 - mean_absolute_error: 0.0046 - val_loss: 6.3168e-05 - val_mean_absolute_error: 0.0058
Epoch 85/100
1/126 [..............................] - ETA: 0s - loss: 2.8763e-05 - mean_absolute_error: 0.0037 23/126 [====>.........................] - ETA: 0s - loss: 3.2718e-05 - mean_absolute_error: 0.0041 45/126 [=========>....................] - ETA: 0s - loss: 3.4196e-05 - mean_absolute_error: 0.0044 67/126 [==============>...............] - ETA: 0s - loss: 3.5113e-05 - mean_absolute_error: 0.0045 89/126 [====================>.........] - ETA: 0s - loss: 3.7361e-05 - mean_absolute_error: 0.0046111/126 [=========================>....] - ETA: 0s - loss: 3.8630e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 3.8327e-05 - mean_absolute_error: 0.0047 - val_loss: 6.2533e-05 - val_mean_absolute_error: 0.0055
Epoch 86/100
1/126 [..............................] - ETA: 0s - loss: 3.2781e-05 - mean_absolute_error: 0.0043 22/126 [====>.........................] - ETA: 0s - loss: 3.4636e-05 - mean_absolute_error: 0.0042 44/126 [=========>....................] - ETA: 0s - loss: 3.5049e-05 - mean_absolute_error: 0.0043 66/126 [==============>...............] - ETA: 0s - loss: 3.2896e-05 - mean_absolute_error: 0.0042 87/126 [===================>..........] - ETA: 0s - loss: 3.2452e-05 - mean_absolute_error: 0.0042108/126 [========================>.....] - ETA: 0s - loss: 3.2966e-05 - mean_absolute_error: 0.0042126/126 [==============================] - 0s 3ms/step - loss: 3.5916e-05 - mean_absolute_error: 0.0044 - val_loss: 1.1160e-04 - val_mean_absolute_error: 0.0084
Epoch 87/100
1/126 [..............................] - ETA: 0s - loss: 9.4774e-05 - mean_absolute_error: 0.0079 23/126 [====>.........................] - ETA: 0s - loss: 4.2020e-05 - mean_absolute_error: 0.0051 45/126 [=========>....................] - ETA: 0s - loss: 4.1111e-05 - mean_absolute_error: 0.0050 67/126 [==============>...............] - ETA: 0s - loss: 3.9884e-05 - mean_absolute_error: 0.0049 88/126 [===================>..........] - ETA: 0s - loss: 3.7823e-05 - mean_absolute_error: 0.0047109/126 [========================>.....] - ETA: 0s - loss: 3.7617e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 4.0297e-05 - mean_absolute_error: 0.0048 - val_loss: 1.0315e-04 - val_mean_absolute_error: 0.0079
Epoch 88/100
1/126 [..............................] - ETA: 0s - loss: 6.6087e-05 - mean_absolute_error: 0.0069 23/126 [====>.........................] - ETA: 0s - loss: 3.9856e-05 - mean_absolute_error: 0.0048 45/126 [=========>....................] - ETA: 0s - loss: 3.6924e-05 - mean_absolute_error: 0.0046 67/126 [==============>...............] - ETA: 0s - loss: 3.8624e-05 - mean_absolute_error: 0.0048 89/126 [====================>.........] - ETA: 0s - loss: 3.8627e-05 - mean_absolute_error: 0.0047110/126 [=========================>....] - ETA: 0s - loss: 3.7724e-05 - mean_absolute_error: 0.0046126/126 [==============================] - 0s 3ms/step - loss: 3.6556e-05 - mean_absolute_error: 0.0045 - val_loss: 8.1166e-05 - val_mean_absolute_error: 0.0071
Epoch 89/100
1/126 [..............................] - ETA: 0s - loss: 4.8642e-05 - mean_absolute_error: 0.0055 22/126 [====>.........................] - ETA: 0s - loss: 3.4134e-05 - mean_absolute_error: 0.0043 43/126 [=========>....................] - ETA: 0s - loss: 3.6619e-05 - mean_absolute_error: 0.0046 63/126 [==============>...............] - ETA: 0s - loss: 3.7763e-05 - mean_absolute_error: 0.0047 84/126 [===================>..........] - ETA: 0s - loss: 3.7688e-05 - mean_absolute_error: 0.0047105/126 [========================>.....] - ETA: 0s - loss: 3.8037e-05 - mean_absolute_error: 0.0047126/126 [==============================] - 0s 3ms/step - loss: 3.8174e-05 - mean_absolute_error: 0.0047 - val_loss: 9.0780e-05 - val_mean_absolute_error: 0.0076
Epoch 90/100
1/126 [..............................] - ETA: 0s - loss: 4.6399e-05 - mean_absolute_error: 0.0054 23/126 [====>.........................] - ETA: 0s - loss: 4.5304e-05 - mean_absolute_error: 0.0054 45/126 [=========>....................] - ETA: 0s - loss: 3.9063e-05 - mean_absolute_error: 0.0048 67/126 [==============>...............] - ETA: 0s - loss: 3.5532e-05 - mean_absolute_error: 0.0044 89/126 [====================>.........] - ETA: 0s - loss: 3.5295e-05 - mean_absolute_error: 0.0044110/126 [=========================>....] - ETA: 0s - loss: 3.5871e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.5693e-05 - mean_absolute_error: 0.0044 - val_loss: 6.6235e-05 - val_mean_absolute_error: 0.0061
Epoch 91/100
1/126 [..............................] - ETA: 0s - loss: 1.5672e-05 - mean_absolute_error: 0.0032 18/126 [===>..........................] - ETA: 0s - loss: 4.0966e-05 - mean_absolute_error: 0.0051 39/126 [========>.....................] - ETA: 0s - loss: 3.9867e-05 - mean_absolute_error: 0.0048 60/126 [=============>................] - ETA: 0s - loss: 3.9010e-05 - mean_absolute_error: 0.0048 81/126 [==================>...........] - ETA: 0s - loss: 3.6643e-05 - mean_absolute_error: 0.0046102/126 [=======================>......] - ETA: 0s - loss: 3.5773e-05 - mean_absolute_error: 0.0044123/126 [============================>.] - ETA: 0s - loss: 3.6553e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.6490e-05 - mean_absolute_error: 0.0045 - val_loss: 6.3068e-05 - val_mean_absolute_error: 0.0058
Epoch 92/100
1/126 [..............................] - ETA: 0s - loss: 2.2826e-05 - mean_absolute_error: 0.0038 23/126 [====>.........................] - ETA: 0s - loss: 2.7748e-05 - mean_absolute_error: 0.0037 44/126 [=========>....................] - ETA: 0s - loss: 3.4383e-05 - mean_absolute_error: 0.0044 65/126 [==============>...............] - ETA: 0s - loss: 3.5928e-05 - mean_absolute_error: 0.0046 86/126 [===================>..........] - ETA: 0s - loss: 3.9663e-05 - mean_absolute_error: 0.0048107/126 [========================>.....] - ETA: 0s - loss: 4.0493e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.0478e-05 - mean_absolute_error: 0.0049 - val_loss: 6.2008e-05 - val_mean_absolute_error: 0.0057
Epoch 93/100
1/126 [..............................] - ETA: 0s - loss: 2.7884e-05 - mean_absolute_error: 0.0041 23/126 [====>.........................] - ETA: 0s - loss: 3.6314e-05 - mean_absolute_error: 0.0045 45/126 [=========>....................] - ETA: 0s - loss: 3.6453e-05 - mean_absolute_error: 0.0045 66/126 [==============>...............] - ETA: 0s - loss: 3.8091e-05 - mean_absolute_error: 0.0047 87/126 [===================>..........] - ETA: 0s - loss: 3.6006e-05 - mean_absolute_error: 0.0045109/126 [========================>.....] - ETA: 0s - loss: 3.5510e-05 - mean_absolute_error: 0.0044126/126 [==============================] - 0s 3ms/step - loss: 3.8626e-05 - mean_absolute_error: 0.0046 - val_loss: 7.3538e-05 - val_mean_absolute_error: 0.0066
Epoch 94/100
1/126 [..............................] - ETA: 0s - loss: 4.3981e-05 - mean_absolute_error: 0.0052 23/126 [====>.........................] - ETA: 0s - loss: 6.0604e-05 - mean_absolute_error: 0.0063 45/126 [=========>....................] - ETA: 0s - loss: 4.9771e-05 - mean_absolute_error: 0.0054 67/126 [==============>...............] - ETA: 0s - loss: 4.3371e-05 - mean_absolute_error: 0.0050 88/126 [===================>..........] - ETA: 0s - loss: 4.1105e-05 - mean_absolute_error: 0.0048110/126 [=========================>....] - ETA: 0s - loss: 4.0632e-05 - mean_absolute_error: 0.0048126/126 [==============================] - 0s 3ms/step - loss: 4.0983e-05 - mean_absolute_error: 0.0049 - val_loss: 9.5146e-05 - val_mean_absolute_error: 0.0079
Epoch 95/100
1/126 [..............................] - ETA: 0s - loss: 3.5332e-05 - mean_absolute_error: 0.0050 22/126 [====>.........................] - ETA: 0s - loss: 5.0619e-05 - mean_absolute_error: 0.0057 43/126 [=========>....................] - ETA: 0s - loss: 5.1466e-05 - mean_absolute_error: 0.0057 64/126 [==============>...............] - ETA: 0s - loss: 5.1218e-05 - mean_absolute_error: 0.0057 86/126 [===================>..........] - ETA: 0s - loss: 4.9961e-05 - mean_absolute_error: 0.0055107/126 [========================>.....] - ETA: 0s - loss: 4.8969e-05 - mean_absolute_error: 0.0055126/126 [==============================] - 0s 3ms/step - loss: 4.6279e-05 - mean_absolute_error: 0.0053 - val_loss: 5.9523e-05 - val_mean_absolute_error: 0.0053
Epoch 96/100
1/126 [..............................] - ETA: 0s - loss: 4.1008e-05 - mean_absolute_error: 0.0046 22/126 [====>.........................] - ETA: 0s - loss: 3.3195e-05 - mean_absolute_error: 0.0043 44/126 [=========>....................] - ETA: 0s - loss: 3.0945e-05 - mean_absolute_error: 0.0040 66/126 [==============>...............] - ETA: 0s - loss: 3.3239e-05 - mean_absolute_error: 0.0041 88/126 [===================>..........] - ETA: 0s - loss: 3.4001e-05 - mean_absolute_error: 0.0042110/126 [=========================>....] - ETA: 0s - loss: 3.3336e-05 - mean_absolute_error: 0.0042126/126 [==============================] - 0s 3ms/step - loss: 3.2969e-05 - mean_absolute_error: 0.0042 - val_loss: 6.5868e-05 - val_mean_absolute_error: 0.0061
Epoch 97/100
1/126 [..............................] - ETA: 0s - loss: 4.6864e-05 - mean_absolute_error: 0.0053 23/126 [====>.........................] - ETA: 0s - loss: 3.4557e-05 - mean_absolute_error: 0.0043 45/126 [=========>....................] - ETA: 0s - loss: 3.6394e-05 - mean_absolute_error: 0.0045 67/126 [==============>...............] - ETA: 0s - loss: 3.4244e-05 - mean_absolute_error: 0.0043 88/126 [===================>..........] - ETA: 0s - loss: 3.2610e-05 - mean_absolute_error: 0.0041109/126 [========================>.....] - ETA: 0s - loss: 3.3438e-05 - mean_absolute_error: 0.0042126/126 [==============================] - 0s 3ms/step - loss: 3.3805e-05 - mean_absolute_error: 0.0042 - val_loss: 6.3434e-05 - val_mean_absolute_error: 0.0057
Epoch 98/100
1/126 [..............................] - ETA: 0s - loss: 4.9038e-05 - mean_absolute_error: 0.0054 22/126 [====>.........................] - ETA: 0s - loss: 3.2829e-05 - mean_absolute_error: 0.0042 44/126 [=========>....................] - ETA: 0s - loss: 3.2078e-05 - mean_absolute_error: 0.0041 65/126 [==============>...............] - ETA: 0s - loss: 3.3659e-05 - mean_absolute_error: 0.0043 86/126 [===================>..........] - ETA: 0s - loss: 3.5003e-05 - mean_absolute_error: 0.0044107/126 [========================>.....] - ETA: 0s - loss: 3.5660e-05 - mean_absolute_error: 0.0045126/126 [==============================] - 0s 3ms/step - loss: 3.5802e-05 - mean_absolute_error: 0.0045 - val_loss: 6.9037e-05 - val_mean_absolute_error: 0.0063
Epoch 99/100
1/126 [..............................] - ETA: 0s - loss: 3.9561e-05 - mean_absolute_error: 0.0051 23/126 [====>.........................] - ETA: 0s - loss: 3.6243e-05 - mean_absolute_error: 0.0045 44/126 [=========>....................] - ETA: 0s - loss: 4.0095e-05 - mean_absolute_error: 0.0048 65/126 [==============>...............] - ETA: 0s - loss: 4.5903e-05 - mean_absolute_error: 0.0052 86/126 [===================>..........] - ETA: 0s - loss: 4.3752e-05 - mean_absolute_error: 0.0051107/126 [========================>.....] - ETA: 0s - loss: 4.1309e-05 - mean_absolute_error: 0.0049126/126 [==============================] - 0s 3ms/step - loss: 4.0839e-05 - mean_absolute_error: 0.0049 - val_loss: 6.8770e-05 - val_mean_absolute_error: 0.0063
Epoch 100/100
1/126 [..............................] - ETA: 0s - loss: 2.7794e-05 - mean_absolute_error: 0.0041 20/126 [===>..........................] - ETA: 0s - loss: 3.7324e-05 - mean_absolute_error: 0.0046 41/126 [========>.....................] - ETA: 0s - loss: 3.3198e-05 - mean_absolute_error: 0.0043 62/126 [=============>................] - ETA: 0s - loss: 3.3299e-05 - mean_absolute_error: 0.0043 83/126 [==================>...........] - ETA: 0s - loss: 3.3179e-05 - mean_absolute_error: 0.0043105/126 [========================>.....] - ETA: 0s - loss: 3.3161e-05 - mean_absolute_error: 0.0043126/126 [==============================] - 0s 3ms/step - loss: 3.4646e-05 - mean_absolute_error: 0.0044 - val_loss: 7.1683e-05 - val_mean_absolute_error: 0.0065
<keras.src.callbacks.History at 0x1b9ccb31810>
After the training and fitting of the Machine Learning model for the United Kingdom, I tried to create visualizations comparing the model against the country’s training dataset, validation dataset, but most importantly the testing dataset (as shown below in the line graphs). Note that the darker and thicker blue lines represent the prediction model’s projections and the thinner red lines is the observed/gathered data.
```{python}
# Testing the Machine Learning Model prediction for United Kingdom with the train,
# validation, and test sets
# Most important is the test set prediction as this tests the effectiveness
# of the Machine Learning model on data it has not seen before
united_kingdom_train_pred = united_kingdom_model.predict(X_united_kingdom_train).flatten()
plt.plot(dates_united_kingdom_train, united_kingdom_train_pred, linewidth=4)
plt.plot(dates_united_kingdom_train, y_united_kingdom_train, linewidth=1)
plt.legend(["Training Predictions", "Training Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("United Kingdom - Training Set Predictions vs. Observations")
plt.show()
united_kingdom_val_pred = united_kingdom_model.predict(X_united_kingdom_val).flatten()
plt.plot(dates_united_kingdom_val, united_kingdom_val_pred, linewidth=4)
plt.plot(dates_united_kingdom_val, y_united_kingdom_val, linewidth=1)
plt.legend(["Validation Predictions", "Validation Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("United Kingdom - Validation Set Predictions vs. Observations")
plt.show()
united_kingdom_test_pred = united_kingdom_model.predict(X_united_kingdom_test).flatten()
plt.plot(dates_united_kingdom_test, united_kingdom_test_pred, linewidth=4)
plt.plot(dates_united_kingdom_test, y_united_kingdom_test, linewidth=1)
plt.legend(["Testing Predictions", "Testing Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("United Kingdom - Testing Set Predictions vs. Observations")
plt.show()
``` 1/126 [..............................] - ETA: 43s 44/126 [=========>....................] - ETA: 0s 86/126 [===================>..........] - ETA: 0s126/126 [==============================] - 0s 1ms/step
1/16 [>.............................] - ETA: 0s16/16 [==============================] - 0s 1ms/step
1/16 [>.............................] - ETA: 0s16/16 [==============================] - 0s 1ms/step
Through careful consideration of all of the prediction-based vs. observation-based contrast visualizations together, I consolidated all of graphics into one singular visualization for you to see below to get a more general perspective of the effectiveness of the Machine Learning model at training and fitting towards predicting the United Kingdom’s international currency rate with the United States.
```{python}
# Plotting United Kingdom's observational (reference) data with the predictions
# of its Machine Learning Model (as a way to visually inspect the effectiveness
# of the model)
plt.plot(dates_united_kingdom_train, united_kingdom_train_pred, linewidth=4)
plt.plot(dates_united_kingdom_train, y_united_kingdom_train, linewidth=1)
plt.plot(dates_united_kingdom_val, united_kingdom_val_pred, linewidth=4)
plt.plot(dates_united_kingdom_val, y_united_kingdom_val, linewidth=1)
plt.plot(dates_united_kingdom_test, united_kingdom_test_pred, linewidth=4)
plt.plot(dates_united_kingdom_test, y_united_kingdom_test, linewidth=1)
plt.legend(["Training Predictions",
"Training Observations",
"Validation Predictions",
"Validation Observations",
"Testing Predictions",
"Testing Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Culmination of the Three Machine Learning Phases of United Kingdom's Dataset - Predictions vs. Observations")
plt.show()
```Lastly, I worked on Switzerland’s data (as shown below):
Since the data (date, X, and y) is split into three np.arrays and to be more efficient, I will manually split Switzerland’s data into train, test, and validation datasets for the Machine Learning model with 80% going to the training dataset, the next 10% going to the validation dataset, and the last 10% going to the test dataset for each np.array respectively.
```{python}
# Splitting Switzerland's data into train, test, and validation sets on 3
# mediums: the X-axis, the y-axis, and the indices (represented by dates)
dates_switzerland_train, X_switzerland_train, y_switzerland_train = dates_switzerland[:percentile_80], X_switzerland[:percentile_80], y_switzerland[:percentile_80]
dates_switzerland_val, X_switzerland_val, y_switzerland_val = dates_switzerland[percentile_80:percentile_90], X_switzerland[percentile_80:percentile_90], y_switzerland[percentile_80:percentile_90]
dates_switzerland_test, X_switzerland_test, y_switzerland_test = dates_switzerland[percentile_90:], X_switzerland[percentile_90:], y_switzerland[percentile_90:]
plt.plot(dates_switzerland_train, y_switzerland_train, linewidth=1)
plt.plot(dates_switzerland_val, y_switzerland_val, linewidth=1)
plt.plot(dates_switzerland_test, y_switzerland_test, linewidth=1)
plt.legend(["Training", "Validation", "Testing"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Split of Switzerland's Data for LSTM Model")
plt.show()
```Now, I began to configure the Machine Learning model. We added Sequential layers: an Input layer 3 by 1 because we will have 3 np.arrays of Input and 1 np.array as output, utilize a LSTM (Long Short-Term Memory) layer of 64 neurons, apply 2 levels of dense layers with 32 neurons and folliowing recommendations online to use the RELU (Rectified Linear Unit) Activiation Function, and I followed up with one last dense layer of 1 neuron as our output layer since we are just trying to linearly-predict the next currency-rate on a near-future date. Once I configured the Sequential layers, we are ready to compile the model, utilzing the mean_square_error as our minimizing loss function, using the Adam optimizer, and comparing our trained model against our data with the mean_absolute_error metric. Lastly, I fitted our model, utilzing our X_train and Y_train datasets for fitting with validation from our X_valid and Y_valid datasets at 100 epochs.
```{python}
# Configuring the Machine Learning Tensorflow Model for Switzerland
switzerland_model = Sequential([layers.Input((3, 1)),
layers.LSTM(64),
layers.Dense(32, activation="relu"),
layers.Dense(32, activation="relu"),
layers.Dense(1)])
switzerland_model.compile(loss="mse",
optimizer=Adam(learning_rate=0.001),
metrics=["mean_absolute_error"])
switzerland_model.fit(X_switzerland_train, y_switzerland_train, validation_data=(X_switzerland_val, y_switzerland_val), epochs=100)
```Epoch 1/100
1/126 [..............................] - ETA: 3:42 - loss: 1.3814 - mean_absolute_error: 1.1562 23/126 [====>.........................] - ETA: 0s - loss: 1.1866 - mean_absolute_error: 1.0566 45/126 [=========>....................] - ETA: 0s - loss: 0.7362 - mean_absolute_error: 0.7472 67/126 [==============>...............] - ETA: 0s - loss: 0.5026 - mean_absolute_error: 0.5439 88/126 [===================>..........] - ETA: 0s - loss: 0.3840 - mean_absolute_error: 0.4292110/126 [=========================>....] - ETA: 0s - loss: 0.3080 - mean_absolute_error: 0.3541126/126 [==============================] - 3s 6ms/step - loss: 0.2707 - mean_absolute_error: 0.3165 - val_loss: 0.0024 - val_mean_absolute_error: 0.0482
Epoch 2/100
1/126 [..............................] - ETA: 0s - loss: 0.0022 - mean_absolute_error: 0.0403 25/126 [====>.........................] - ETA: 0s - loss: 0.0026 - mean_absolute_error: 0.0423 48/126 [==========>...................] - ETA: 0s - loss: 0.0023 - mean_absolute_error: 0.0401 71/126 [===============>..............] - ETA: 0s - loss: 0.0021 - mean_absolute_error: 0.0378 94/126 [=====================>........] - ETA: 0s - loss: 0.0018 - mean_absolute_error: 0.0350116/126 [==========================>...] - ETA: 0s - loss: 0.0016 - mean_absolute_error: 0.0328126/126 [==============================] - 0s 3ms/step - loss: 0.0016 - mean_absolute_error: 0.0319 - val_loss: 3.6963e-04 - val_mean_absolute_error: 0.0179
Epoch 3/100
1/126 [..............................] - ETA: 0s - loss: 5.0520e-04 - mean_absolute_error: 0.0186 24/126 [====>.........................] - ETA: 0s - loss: 5.0059e-04 - mean_absolute_error: 0.0178 46/126 [=========>....................] - ETA: 0s - loss: 4.2590e-04 - mean_absolute_error: 0.0166 68/126 [===============>..............] - ETA: 0s - loss: 3.8753e-04 - mean_absolute_error: 0.0157 90/126 [====================>.........] - ETA: 0s - loss: 3.4043e-04 - mean_absolute_error: 0.0146112/126 [=========================>....] - ETA: 0s - loss: 3.0637e-04 - mean_absolute_error: 0.0137126/126 [==============================] - 0s 3ms/step - loss: 2.9146e-04 - mean_absolute_error: 0.0133 - val_loss: 7.2633e-05 - val_mean_absolute_error: 0.0069
Epoch 4/100
1/126 [..............................] - ETA: 0s - loss: 1.3796e-04 - mean_absolute_error: 0.0096 23/126 [====>.........................] - ETA: 0s - loss: 1.5241e-04 - mean_absolute_error: 0.0096 45/126 [=========>....................] - ETA: 0s - loss: 1.5113e-04 - mean_absolute_error: 0.0096 68/126 [===============>..............] - ETA: 0s - loss: 1.5429e-04 - mean_absolute_error: 0.0097 91/126 [====================>.........] - ETA: 0s - loss: 1.6156e-04 - mean_absolute_error: 0.0097112/126 [=========================>....] - ETA: 0s - loss: 1.6177e-04 - mean_absolute_error: 0.0096126/126 [==============================] - 0s 3ms/step - loss: 1.6021e-04 - mean_absolute_error: 0.0096 - val_loss: 5.0084e-05 - val_mean_absolute_error: 0.0055
Epoch 5/100
1/126 [..............................] - ETA: 0s - loss: 1.8628e-04 - mean_absolute_error: 0.0114 23/126 [====>.........................] - ETA: 0s - loss: 1.6925e-04 - mean_absolute_error: 0.0096 45/126 [=========>....................] - ETA: 0s - loss: 1.6328e-04 - mean_absolute_error: 0.0096 66/126 [==============>...............] - ETA: 0s - loss: 1.5673e-04 - mean_absolute_error: 0.0094 87/126 [===================>..........] - ETA: 0s - loss: 1.5678e-04 - mean_absolute_error: 0.0094108/126 [========================>.....] - ETA: 0s - loss: 1.6371e-04 - mean_absolute_error: 0.0096126/126 [==============================] - 0s 3ms/step - loss: 1.6171e-04 - mean_absolute_error: 0.0096 - val_loss: 5.3686e-05 - val_mean_absolute_error: 0.0059
Epoch 6/100
1/126 [..............................] - ETA: 0s - loss: 1.6053e-04 - mean_absolute_error: 0.0100 23/126 [====>.........................] - ETA: 0s - loss: 1.7667e-04 - mean_absolute_error: 0.0097 46/126 [=========>....................] - ETA: 0s - loss: 1.6032e-04 - mean_absolute_error: 0.0095 68/126 [===============>..............] - ETA: 0s - loss: 1.5739e-04 - mean_absolute_error: 0.0095 89/126 [====================>.........] - ETA: 0s - loss: 1.5776e-04 - mean_absolute_error: 0.0094109/126 [========================>.....] - ETA: 0s - loss: 1.5632e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5563e-04 - mean_absolute_error: 0.0094 - val_loss: 4.9900e-05 - val_mean_absolute_error: 0.0055
Epoch 7/100
1/126 [..............................] - ETA: 0s - loss: 9.7115e-05 - mean_absolute_error: 0.0077 22/126 [====>.........................] - ETA: 0s - loss: 1.5574e-04 - mean_absolute_error: 0.0095 44/126 [=========>....................] - ETA: 0s - loss: 1.6275e-04 - mean_absolute_error: 0.0094 66/126 [==============>...............] - ETA: 0s - loss: 1.5817e-04 - mean_absolute_error: 0.0094 88/126 [===================>..........] - ETA: 0s - loss: 1.6011e-04 - mean_absolute_error: 0.0094110/126 [=========================>....] - ETA: 0s - loss: 1.5798e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5466e-04 - mean_absolute_error: 0.0094 - val_loss: 4.9407e-05 - val_mean_absolute_error: 0.0054
Epoch 8/100
1/126 [..............................] - ETA: 0s - loss: 1.5897e-04 - mean_absolute_error: 0.0096 23/126 [====>.........................] - ETA: 0s - loss: 1.8162e-04 - mean_absolute_error: 0.0098 45/126 [=========>....................] - ETA: 0s - loss: 1.7448e-04 - mean_absolute_error: 0.0097 67/126 [==============>...............] - ETA: 0s - loss: 1.6468e-04 - mean_absolute_error: 0.0096 88/126 [===================>..........] - ETA: 0s - loss: 1.6056e-04 - mean_absolute_error: 0.0095110/126 [=========================>....] - ETA: 0s - loss: 1.5808e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.5535e-04 - mean_absolute_error: 0.0094 - val_loss: 4.9746e-05 - val_mean_absolute_error: 0.0055
Epoch 9/100
1/126 [..............................] - ETA: 0s - loss: 1.0584e-04 - mean_absolute_error: 0.0084 23/126 [====>.........................] - ETA: 0s - loss: 1.4771e-04 - mean_absolute_error: 0.0094 44/126 [=========>....................] - ETA: 0s - loss: 1.7493e-04 - mean_absolute_error: 0.0099 67/126 [==============>...............] - ETA: 0s - loss: 1.6340e-04 - mean_absolute_error: 0.0097 89/126 [====================>.........] - ETA: 0s - loss: 1.6695e-04 - mean_absolute_error: 0.0097110/126 [=========================>....] - ETA: 0s - loss: 1.6249e-04 - mean_absolute_error: 0.0096126/126 [==============================] - 0s 3ms/step - loss: 1.6071e-04 - mean_absolute_error: 0.0096 - val_loss: 5.9952e-05 - val_mean_absolute_error: 0.0062
Epoch 10/100
1/126 [..............................] - ETA: 0s - loss: 1.5238e-04 - mean_absolute_error: 0.0104 23/126 [====>.........................] - ETA: 0s - loss: 1.6097e-04 - mean_absolute_error: 0.0096 45/126 [=========>....................] - ETA: 0s - loss: 1.7563e-04 - mean_absolute_error: 0.0097 67/126 [==============>...............] - ETA: 0s - loss: 1.6742e-04 - mean_absolute_error: 0.0097 89/126 [====================>.........] - ETA: 0s - loss: 1.6101e-04 - mean_absolute_error: 0.0096111/126 [=========================>....] - ETA: 0s - loss: 1.5916e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.6167e-04 - mean_absolute_error: 0.0095 - val_loss: 5.4379e-05 - val_mean_absolute_error: 0.0059
Epoch 11/100
1/126 [..............................] - ETA: 0s - loss: 1.9129e-04 - mean_absolute_error: 0.0110 23/126 [====>.........................] - ETA: 0s - loss: 1.4233e-04 - mean_absolute_error: 0.0094 45/126 [=========>....................] - ETA: 0s - loss: 1.4403e-04 - mean_absolute_error: 0.0093 67/126 [==============>...............] - ETA: 0s - loss: 1.5125e-04 - mean_absolute_error: 0.0093 90/126 [====================>.........] - ETA: 0s - loss: 1.4747e-04 - mean_absolute_error: 0.0092112/126 [=========================>....] - ETA: 0s - loss: 1.4796e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.5387e-04 - mean_absolute_error: 0.0093 - val_loss: 4.9471e-05 - val_mean_absolute_error: 0.0054
Epoch 12/100
1/126 [..............................] - ETA: 0s - loss: 1.2975e-04 - mean_absolute_error: 0.0091 24/126 [====>.........................] - ETA: 0s - loss: 1.6911e-04 - mean_absolute_error: 0.0099 47/126 [==========>...................] - ETA: 0s - loss: 1.7792e-04 - mean_absolute_error: 0.0100 69/126 [===============>..............] - ETA: 0s - loss: 1.7258e-04 - mean_absolute_error: 0.0098 92/126 [====================>.........] - ETA: 0s - loss: 1.6349e-04 - mean_absolute_error: 0.0096114/126 [==========================>...] - ETA: 0s - loss: 1.6653e-04 - mean_absolute_error: 0.0097126/126 [==============================] - 0s 3ms/step - loss: 1.6281e-04 - mean_absolute_error: 0.0096 - val_loss: 5.2554e-05 - val_mean_absolute_error: 0.0058
Epoch 13/100
1/126 [..............................] - ETA: 0s - loss: 1.5515e-04 - mean_absolute_error: 0.0103 23/126 [====>.........................] - ETA: 0s - loss: 1.4751e-04 - mean_absolute_error: 0.0093 45/126 [=========>....................] - ETA: 0s - loss: 1.5991e-04 - mean_absolute_error: 0.0096 67/126 [==============>...............] - ETA: 0s - loss: 1.5243e-04 - mean_absolute_error: 0.0094 88/126 [===================>..........] - ETA: 0s - loss: 1.6026e-04 - mean_absolute_error: 0.0095109/126 [========================>.....] - ETA: 0s - loss: 1.5859e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.5663e-04 - mean_absolute_error: 0.0095 - val_loss: 5.4029e-05 - val_mean_absolute_error: 0.0059
Epoch 14/100
1/126 [..............................] - ETA: 0s - loss: 1.2373e-04 - mean_absolute_error: 0.0093 23/126 [====>.........................] - ETA: 0s - loss: 1.4524e-04 - mean_absolute_error: 0.0093 45/126 [=========>....................] - ETA: 0s - loss: 1.3907e-04 - mean_absolute_error: 0.0091 67/126 [==============>...............] - ETA: 0s - loss: 1.5158e-04 - mean_absolute_error: 0.0092 88/126 [===================>..........] - ETA: 0s - loss: 1.5176e-04 - mean_absolute_error: 0.0093109/126 [========================>.....] - ETA: 0s - loss: 1.4946e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.5166e-04 - mean_absolute_error: 0.0092 - val_loss: 4.9316e-05 - val_mean_absolute_error: 0.0054
Epoch 15/100
1/126 [..............................] - ETA: 0s - loss: 1.1977e-04 - mean_absolute_error: 0.0085 23/126 [====>.........................] - ETA: 0s - loss: 1.4443e-04 - mean_absolute_error: 0.0091 45/126 [=========>....................] - ETA: 0s - loss: 1.5176e-04 - mean_absolute_error: 0.0090 67/126 [==============>...............] - ETA: 0s - loss: 1.4772e-04 - mean_absolute_error: 0.0091 88/126 [===================>..........] - ETA: 0s - loss: 1.4643e-04 - mean_absolute_error: 0.0091109/126 [========================>.....] - ETA: 0s - loss: 1.4859e-04 - mean_absolute_error: 0.0091126/126 [==============================] - 0s 3ms/step - loss: 1.5023e-04 - mean_absolute_error: 0.0092 - val_loss: 5.1415e-05 - val_mean_absolute_error: 0.0057
Epoch 16/100
1/126 [..............................] - ETA: 0s - loss: 1.4571e-04 - mean_absolute_error: 0.0087 24/126 [====>.........................] - ETA: 0s - loss: 1.5671e-04 - mean_absolute_error: 0.0091 46/126 [=========>....................] - ETA: 0s - loss: 1.5105e-04 - mean_absolute_error: 0.0092 68/126 [===============>..............] - ETA: 0s - loss: 1.5515e-04 - mean_absolute_error: 0.0092 91/126 [====================>.........] - ETA: 0s - loss: 1.5199e-04 - mean_absolute_error: 0.0092113/126 [=========================>....] - ETA: 0s - loss: 1.4970e-04 - mean_absolute_error: 0.0091126/126 [==============================] - 0s 3ms/step - loss: 1.4881e-04 - mean_absolute_error: 0.0091 - val_loss: 4.9972e-05 - val_mean_absolute_error: 0.0055
Epoch 17/100
1/126 [..............................] - ETA: 0s - loss: 1.2227e-04 - mean_absolute_error: 0.0093 23/126 [====>.........................] - ETA: 0s - loss: 1.4813e-04 - mean_absolute_error: 0.0094 45/126 [=========>....................] - ETA: 0s - loss: 1.5190e-04 - mean_absolute_error: 0.0095 67/126 [==============>...............] - ETA: 0s - loss: 1.6673e-04 - mean_absolute_error: 0.0098 89/126 [====================>.........] - ETA: 0s - loss: 1.6094e-04 - mean_absolute_error: 0.0097111/126 [=========================>....] - ETA: 0s - loss: 1.6110e-04 - mean_absolute_error: 0.0096126/126 [==============================] - 0s 3ms/step - loss: 1.5755e-04 - mean_absolute_error: 0.0095 - val_loss: 5.8704e-05 - val_mean_absolute_error: 0.0062
Epoch 18/100
1/126 [..............................] - ETA: 0s - loss: 1.3579e-04 - mean_absolute_error: 0.0096 24/126 [====>.........................] - ETA: 0s - loss: 1.3269e-04 - mean_absolute_error: 0.0087 46/126 [=========>....................] - ETA: 0s - loss: 1.3999e-04 - mean_absolute_error: 0.0091 68/126 [===============>..............] - ETA: 0s - loss: 1.5626e-04 - mean_absolute_error: 0.0093 90/126 [====================>.........] - ETA: 0s - loss: 1.5697e-04 - mean_absolute_error: 0.0094111/126 [=========================>....] - ETA: 0s - loss: 1.5332e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5680e-04 - mean_absolute_error: 0.0094 - val_loss: 4.9308e-05 - val_mean_absolute_error: 0.0054
Epoch 19/100
1/126 [..............................] - ETA: 0s - loss: 1.2599e-04 - mean_absolute_error: 0.0091 23/126 [====>.........................] - ETA: 0s - loss: 1.3048e-04 - mean_absolute_error: 0.0087 45/126 [=========>....................] - ETA: 0s - loss: 1.3605e-04 - mean_absolute_error: 0.0089 65/126 [==============>...............] - ETA: 0s - loss: 1.5033e-04 - mean_absolute_error: 0.0091 85/126 [===================>..........] - ETA: 0s - loss: 1.5447e-04 - mean_absolute_error: 0.0092106/126 [========================>.....] - ETA: 0s - loss: 1.5714e-04 - mean_absolute_error: 0.0093126/126 [==============================] - 0s 3ms/step - loss: 1.5366e-04 - mean_absolute_error: 0.0093 - val_loss: 5.0093e-05 - val_mean_absolute_error: 0.0055
Epoch 20/100
1/126 [..............................] - ETA: 0s - loss: 9.1638e-05 - mean_absolute_error: 0.0077 23/126 [====>.........................] - ETA: 0s - loss: 1.6929e-04 - mean_absolute_error: 0.0098 45/126 [=========>....................] - ETA: 0s - loss: 1.6229e-04 - mean_absolute_error: 0.0094 68/126 [===============>..............] - ETA: 0s - loss: 1.5815e-04 - mean_absolute_error: 0.0094 89/126 [====================>.........] - ETA: 0s - loss: 1.6578e-04 - mean_absolute_error: 0.0096111/126 [=========================>....] - ETA: 0s - loss: 1.5659e-04 - mean_absolute_error: 0.0093126/126 [==============================] - 0s 3ms/step - loss: 1.5216e-04 - mean_absolute_error: 0.0092 - val_loss: 6.3317e-05 - val_mean_absolute_error: 0.0064
Epoch 21/100
1/126 [..............................] - ETA: 0s - loss: 1.5423e-04 - mean_absolute_error: 0.0099 23/126 [====>.........................] - ETA: 0s - loss: 2.1462e-04 - mean_absolute_error: 0.0108 46/126 [=========>....................] - ETA: 0s - loss: 1.8412e-04 - mean_absolute_error: 0.0102 69/126 [===============>..............] - ETA: 0s - loss: 1.6632e-04 - mean_absolute_error: 0.0097 91/126 [====================>.........] - ETA: 0s - loss: 1.5829e-04 - mean_absolute_error: 0.0095113/126 [=========================>....] - ETA: 0s - loss: 1.5833e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5591e-04 - mean_absolute_error: 0.0094 - val_loss: 5.0218e-05 - val_mean_absolute_error: 0.0055
Epoch 22/100
1/126 [..............................] - ETA: 0s - loss: 9.8867e-05 - mean_absolute_error: 0.0083 23/126 [====>.........................] - ETA: 0s - loss: 1.2898e-04 - mean_absolute_error: 0.0087 45/126 [=========>....................] - ETA: 0s - loss: 1.6123e-04 - mean_absolute_error: 0.0094 67/126 [==============>...............] - ETA: 0s - loss: 1.6046e-04 - mean_absolute_error: 0.0095 90/126 [====================>.........] - ETA: 0s - loss: 1.5757e-04 - mean_absolute_error: 0.0093112/126 [=========================>....] - ETA: 0s - loss: 1.5335e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.5134e-04 - mean_absolute_error: 0.0092 - val_loss: 5.3611e-05 - val_mean_absolute_error: 0.0058
Epoch 23/100
1/126 [..............................] - ETA: 0s - loss: 7.9575e-05 - mean_absolute_error: 0.0071 23/126 [====>.........................] - ETA: 0s - loss: 1.3062e-04 - mean_absolute_error: 0.0087 45/126 [=========>....................] - ETA: 0s - loss: 1.2614e-04 - mean_absolute_error: 0.0086 67/126 [==============>...............] - ETA: 0s - loss: 1.5233e-04 - mean_absolute_error: 0.0092 89/126 [====================>.........] - ETA: 0s - loss: 1.4493e-04 - mean_absolute_error: 0.0090111/126 [=========================>....] - ETA: 0s - loss: 1.4829e-04 - mean_absolute_error: 0.0090126/126 [==============================] - 0s 3ms/step - loss: 1.4647e-04 - mean_absolute_error: 0.0090 - val_loss: 5.4809e-05 - val_mean_absolute_error: 0.0059
Epoch 24/100
1/126 [..............................] - ETA: 0s - loss: 1.1027e-04 - mean_absolute_error: 0.0079 24/126 [====>.........................] - ETA: 0s - loss: 1.3222e-04 - mean_absolute_error: 0.0088 46/126 [=========>....................] - ETA: 0s - loss: 1.3518e-04 - mean_absolute_error: 0.0088 68/126 [===============>..............] - ETA: 0s - loss: 1.3679e-04 - mean_absolute_error: 0.0089 90/126 [====================>.........] - ETA: 0s - loss: 1.3873e-04 - mean_absolute_error: 0.0090112/126 [=========================>....] - ETA: 0s - loss: 1.3947e-04 - mean_absolute_error: 0.0090126/126 [==============================] - 0s 3ms/step - loss: 1.4869e-04 - mean_absolute_error: 0.0091 - val_loss: 5.4606e-05 - val_mean_absolute_error: 0.0059
Epoch 25/100
1/126 [..............................] - ETA: 0s - loss: 2.6196e-04 - mean_absolute_error: 0.0113 23/126 [====>.........................] - ETA: 0s - loss: 2.0436e-04 - mean_absolute_error: 0.0102 45/126 [=========>....................] - ETA: 0s - loss: 1.8118e-04 - mean_absolute_error: 0.0099 66/126 [==============>...............] - ETA: 0s - loss: 1.7164e-04 - mean_absolute_error: 0.0096 88/126 [===================>..........] - ETA: 0s - loss: 1.6533e-04 - mean_absolute_error: 0.0096110/126 [=========================>....] - ETA: 0s - loss: 1.6152e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.5836e-04 - mean_absolute_error: 0.0094 - val_loss: 4.9816e-05 - val_mean_absolute_error: 0.0055
Epoch 26/100
1/126 [..............................] - ETA: 0s - loss: 1.4377e-04 - mean_absolute_error: 0.0090 23/126 [====>.........................] - ETA: 0s - loss: 1.2541e-04 - mean_absolute_error: 0.0086 44/126 [=========>....................] - ETA: 0s - loss: 1.6138e-04 - mean_absolute_error: 0.0094 66/126 [==============>...............] - ETA: 0s - loss: 1.6353e-04 - mean_absolute_error: 0.0095 88/126 [===================>..........] - ETA: 0s - loss: 1.7557e-04 - mean_absolute_error: 0.0099110/126 [=========================>....] - ETA: 0s - loss: 1.6700e-04 - mean_absolute_error: 0.0097126/126 [==============================] - 0s 3ms/step - loss: 1.6192e-04 - mean_absolute_error: 0.0096 - val_loss: 5.8702e-05 - val_mean_absolute_error: 0.0061
Epoch 27/100
1/126 [..............................] - ETA: 0s - loss: 1.1282e-04 - mean_absolute_error: 0.0080 24/126 [====>.........................] - ETA: 0s - loss: 1.2482e-04 - mean_absolute_error: 0.0087 46/126 [=========>....................] - ETA: 0s - loss: 1.3808e-04 - mean_absolute_error: 0.0090 68/126 [===============>..............] - ETA: 0s - loss: 1.4127e-04 - mean_absolute_error: 0.0089 89/126 [====================>.........] - ETA: 0s - loss: 1.3957e-04 - mean_absolute_error: 0.0089111/126 [=========================>....] - ETA: 0s - loss: 1.4100e-04 - mean_absolute_error: 0.0089126/126 [==============================] - 0s 3ms/step - loss: 1.4457e-04 - mean_absolute_error: 0.0090 - val_loss: 5.4008e-05 - val_mean_absolute_error: 0.0059
Epoch 28/100
1/126 [..............................] - ETA: 0s - loss: 8.8763e-05 - mean_absolute_error: 0.0080 23/126 [====>.........................] - ETA: 0s - loss: 1.6106e-04 - mean_absolute_error: 0.0099 45/126 [=========>....................] - ETA: 0s - loss: 1.8328e-04 - mean_absolute_error: 0.0106 67/126 [==============>...............] - ETA: 0s - loss: 1.6685e-04 - mean_absolute_error: 0.0100 89/126 [====================>.........] - ETA: 0s - loss: 1.5605e-04 - mean_absolute_error: 0.0097111/126 [=========================>....] - ETA: 0s - loss: 1.5594e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.6097e-04 - mean_absolute_error: 0.0096 - val_loss: 1.4948e-04 - val_mean_absolute_error: 0.0104
Epoch 29/100
1/126 [..............................] - ETA: 0s - loss: 4.3305e-04 - mean_absolute_error: 0.0164 23/126 [====>.........................] - ETA: 0s - loss: 2.0170e-04 - mean_absolute_error: 0.0109 45/126 [=========>....................] - ETA: 0s - loss: 1.7994e-04 - mean_absolute_error: 0.0102 67/126 [==============>...............] - ETA: 0s - loss: 1.7311e-04 - mean_absolute_error: 0.0100 89/126 [====================>.........] - ETA: 0s - loss: 1.7155e-04 - mean_absolute_error: 0.0100111/126 [=========================>....] - ETA: 0s - loss: 1.8026e-04 - mean_absolute_error: 0.0102126/126 [==============================] - 0s 3ms/step - loss: 1.8124e-04 - mean_absolute_error: 0.0101 - val_loss: 5.8033e-05 - val_mean_absolute_error: 0.0061
Epoch 30/100
1/126 [..............................] - ETA: 0s - loss: 2.7088e-04 - mean_absolute_error: 0.0126 23/126 [====>.........................] - ETA: 0s - loss: 1.3693e-04 - mean_absolute_error: 0.0089 45/126 [=========>....................] - ETA: 0s - loss: 1.4176e-04 - mean_absolute_error: 0.0091 68/126 [===============>..............] - ETA: 0s - loss: 1.6023e-04 - mean_absolute_error: 0.0095 91/126 [====================>.........] - ETA: 0s - loss: 1.5395e-04 - mean_absolute_error: 0.0094113/126 [=========================>....] - ETA: 0s - loss: 1.5434e-04 - mean_absolute_error: 0.0093126/126 [==============================] - 0s 3ms/step - loss: 1.5462e-04 - mean_absolute_error: 0.0094 - val_loss: 5.3792e-05 - val_mean_absolute_error: 0.0059
Epoch 31/100
1/126 [..............................] - ETA: 0s - loss: 1.2468e-04 - mean_absolute_error: 0.0088 24/126 [====>.........................] - ETA: 0s - loss: 1.6895e-04 - mean_absolute_error: 0.0101 47/126 [==========>...................] - ETA: 0s - loss: 1.5710e-04 - mean_absolute_error: 0.0097 70/126 [===============>..............] - ETA: 0s - loss: 1.6883e-04 - mean_absolute_error: 0.0098 92/126 [====================>.........] - ETA: 0s - loss: 1.7680e-04 - mean_absolute_error: 0.0100113/126 [=========================>....] - ETA: 0s - loss: 1.6857e-04 - mean_absolute_error: 0.0098126/126 [==============================] - 0s 3ms/step - loss: 1.6415e-04 - mean_absolute_error: 0.0097 - val_loss: 7.8361e-05 - val_mean_absolute_error: 0.0073
Epoch 32/100
1/126 [..............................] - ETA: 0s - loss: 1.5570e-04 - mean_absolute_error: 0.0097 23/126 [====>.........................] - ETA: 0s - loss: 1.4209e-04 - mean_absolute_error: 0.0092 46/126 [=========>....................] - ETA: 0s - loss: 1.5732e-04 - mean_absolute_error: 0.0096 67/126 [==============>...............] - ETA: 0s - loss: 1.6820e-04 - mean_absolute_error: 0.0096 89/126 [====================>.........] - ETA: 0s - loss: 1.6015e-04 - mean_absolute_error: 0.0095111/126 [=========================>....] - ETA: 0s - loss: 1.5725e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5767e-04 - mean_absolute_error: 0.0094 - val_loss: 5.8241e-05 - val_mean_absolute_error: 0.0061
Epoch 33/100
1/126 [..............................] - ETA: 0s - loss: 1.9486e-04 - mean_absolute_error: 0.0110 24/126 [====>.........................] - ETA: 0s - loss: 1.6662e-04 - mean_absolute_error: 0.0097 46/126 [=========>....................] - ETA: 0s - loss: 1.7363e-04 - mean_absolute_error: 0.0098 68/126 [===============>..............] - ETA: 0s - loss: 1.8704e-04 - mean_absolute_error: 0.0104 90/126 [====================>.........] - ETA: 0s - loss: 1.7268e-04 - mean_absolute_error: 0.0100112/126 [=========================>....] - ETA: 0s - loss: 1.7410e-04 - mean_absolute_error: 0.0101126/126 [==============================] - 0s 3ms/step - loss: 1.8494e-04 - mean_absolute_error: 0.0103 - val_loss: 5.7045e-05 - val_mean_absolute_error: 0.0060
Epoch 34/100
1/126 [..............................] - ETA: 0s - loss: 8.9926e-05 - mean_absolute_error: 0.0078 23/126 [====>.........................] - ETA: 0s - loss: 1.3804e-04 - mean_absolute_error: 0.0090 46/126 [=========>....................] - ETA: 0s - loss: 1.7008e-04 - mean_absolute_error: 0.0097 68/126 [===============>..............] - ETA: 0s - loss: 1.7229e-04 - mean_absolute_error: 0.0099 89/126 [====================>.........] - ETA: 0s - loss: 1.6442e-04 - mean_absolute_error: 0.0097110/126 [=========================>....] - ETA: 0s - loss: 1.6106e-04 - mean_absolute_error: 0.0096126/126 [==============================] - 0s 3ms/step - loss: 1.6126e-04 - mean_absolute_error: 0.0096 - val_loss: 1.2052e-04 - val_mean_absolute_error: 0.0093
Epoch 35/100
1/126 [..............................] - ETA: 0s - loss: 2.4319e-04 - mean_absolute_error: 0.0131 23/126 [====>.........................] - ETA: 0s - loss: 1.9136e-04 - mean_absolute_error: 0.0101 45/126 [=========>....................] - ETA: 0s - loss: 1.6660e-04 - mean_absolute_error: 0.0093 67/126 [==============>...............] - ETA: 0s - loss: 1.5716e-04 - mean_absolute_error: 0.0092 88/126 [===================>..........] - ETA: 0s - loss: 1.6074e-04 - mean_absolute_error: 0.0094110/126 [=========================>....] - ETA: 0s - loss: 1.5881e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.5921e-04 - mean_absolute_error: 0.0095 - val_loss: 1.4568e-04 - val_mean_absolute_error: 0.0104
Epoch 36/100
1/126 [..............................] - ETA: 0s - loss: 3.5867e-04 - mean_absolute_error: 0.0145 23/126 [====>.........................] - ETA: 0s - loss: 2.5970e-04 - mean_absolute_error: 0.0123 45/126 [=========>....................] - ETA: 0s - loss: 2.0453e-04 - mean_absolute_error: 0.0108 68/126 [===============>..............] - ETA: 0s - loss: 1.8730e-04 - mean_absolute_error: 0.0103 90/126 [====================>.........] - ETA: 0s - loss: 1.9365e-04 - mean_absolute_error: 0.0106112/126 [=========================>....] - ETA: 0s - loss: 1.8825e-04 - mean_absolute_error: 0.0104126/126 [==============================] - 0s 3ms/step - loss: 1.8265e-04 - mean_absolute_error: 0.0102 - val_loss: 6.2905e-05 - val_mean_absolute_error: 0.0064
Epoch 37/100
1/126 [..............................] - ETA: 0s - loss: 8.1368e-05 - mean_absolute_error: 0.0065 23/126 [====>.........................] - ETA: 0s - loss: 1.6124e-04 - mean_absolute_error: 0.0092 45/126 [=========>....................] - ETA: 0s - loss: 1.5255e-04 - mean_absolute_error: 0.0090 67/126 [==============>...............] - ETA: 0s - loss: 1.6280e-04 - mean_absolute_error: 0.0093 90/126 [====================>.........] - ETA: 0s - loss: 1.6036e-04 - mean_absolute_error: 0.0094111/126 [=========================>....] - ETA: 0s - loss: 1.5819e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5745e-04 - mean_absolute_error: 0.0094 - val_loss: 5.0561e-05 - val_mean_absolute_error: 0.0056
Epoch 38/100
1/126 [..............................] - ETA: 0s - loss: 1.1615e-04 - mean_absolute_error: 0.0084 23/126 [====>.........................] - ETA: 0s - loss: 1.9429e-04 - mean_absolute_error: 0.0105 45/126 [=========>....................] - ETA: 0s - loss: 1.8617e-04 - mean_absolute_error: 0.0104 67/126 [==============>...............] - ETA: 0s - loss: 1.6498e-04 - mean_absolute_error: 0.0097 89/126 [====================>.........] - ETA: 0s - loss: 1.6393e-04 - mean_absolute_error: 0.0096111/126 [=========================>....] - ETA: 0s - loss: 1.5760e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5857e-04 - mean_absolute_error: 0.0095 - val_loss: 5.3802e-05 - val_mean_absolute_error: 0.0059
Epoch 39/100
1/126 [..............................] - ETA: 0s - loss: 1.4420e-04 - mean_absolute_error: 0.0093 23/126 [====>.........................] - ETA: 0s - loss: 1.3887e-04 - mean_absolute_error: 0.0091 45/126 [=========>....................] - ETA: 0s - loss: 1.5689e-04 - mean_absolute_error: 0.0091 68/126 [===============>..............] - ETA: 0s - loss: 1.5097e-04 - mean_absolute_error: 0.0091 90/126 [====================>.........] - ETA: 0s - loss: 1.5669e-04 - mean_absolute_error: 0.0094111/126 [=========================>....] - ETA: 0s - loss: 1.5697e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.5907e-04 - mean_absolute_error: 0.0095 - val_loss: 1.1715e-04 - val_mean_absolute_error: 0.0092
Epoch 40/100
1/126 [..............................] - ETA: 0s - loss: 3.6107e-04 - mean_absolute_error: 0.0134 23/126 [====>.........................] - ETA: 0s - loss: 1.6134e-04 - mean_absolute_error: 0.0090 46/126 [=========>....................] - ETA: 0s - loss: 1.4993e-04 - mean_absolute_error: 0.0091 68/126 [===============>..............] - ETA: 0s - loss: 1.6249e-04 - mean_absolute_error: 0.0093 89/126 [====================>.........] - ETA: 0s - loss: 1.5666e-04 - mean_absolute_error: 0.0093109/126 [========================>.....] - ETA: 0s - loss: 1.5231e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.4809e-04 - mean_absolute_error: 0.0091 - val_loss: 5.8095e-05 - val_mean_absolute_error: 0.0061
Epoch 41/100
1/126 [..............................] - ETA: 0s - loss: 1.2071e-04 - mean_absolute_error: 0.0087 24/126 [====>.........................] - ETA: 0s - loss: 1.6905e-04 - mean_absolute_error: 0.0095 46/126 [=========>....................] - ETA: 0s - loss: 1.6933e-04 - mean_absolute_error: 0.0095 68/126 [===============>..............] - ETA: 0s - loss: 1.9641e-04 - mean_absolute_error: 0.0105 90/126 [====================>.........] - ETA: 0s - loss: 1.8910e-04 - mean_absolute_error: 0.0104112/126 [=========================>....] - ETA: 0s - loss: 1.7554e-04 - mean_absolute_error: 0.0100126/126 [==============================] - 0s 3ms/step - loss: 1.7158e-04 - mean_absolute_error: 0.0099 - val_loss: 8.5351e-05 - val_mean_absolute_error: 0.0076
Epoch 42/100
1/126 [..............................] - ETA: 0s - loss: 1.0889e-04 - mean_absolute_error: 0.0092 23/126 [====>.........................] - ETA: 0s - loss: 1.3978e-04 - mean_absolute_error: 0.0092 45/126 [=========>....................] - ETA: 0s - loss: 1.4071e-04 - mean_absolute_error: 0.0092 67/126 [==============>...............] - ETA: 0s - loss: 1.4930e-04 - mean_absolute_error: 0.0094 89/126 [====================>.........] - ETA: 0s - loss: 1.6415e-04 - mean_absolute_error: 0.0098111/126 [=========================>....] - ETA: 0s - loss: 1.6826e-04 - mean_absolute_error: 0.0097126/126 [==============================] - 0s 3ms/step - loss: 1.7525e-04 - mean_absolute_error: 0.0100 - val_loss: 1.3323e-04 - val_mean_absolute_error: 0.0098
Epoch 43/100
1/126 [..............................] - ETA: 0s - loss: 2.2119e-04 - mean_absolute_error: 0.0128 24/126 [====>.........................] - ETA: 0s - loss: 1.5586e-04 - mean_absolute_error: 0.0099 46/126 [=========>....................] - ETA: 0s - loss: 1.6026e-04 - mean_absolute_error: 0.0096 68/126 [===============>..............] - ETA: 0s - loss: 1.6465e-04 - mean_absolute_error: 0.0096 90/126 [====================>.........] - ETA: 0s - loss: 1.5591e-04 - mean_absolute_error: 0.0094111/126 [=========================>....] - ETA: 0s - loss: 1.5816e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5915e-04 - mean_absolute_error: 0.0095 - val_loss: 9.9370e-05 - val_mean_absolute_error: 0.0083
Epoch 44/100
1/126 [..............................] - ETA: 0s - loss: 1.8137e-04 - mean_absolute_error: 0.0098 23/126 [====>.........................] - ETA: 0s - loss: 1.6780e-04 - mean_absolute_error: 0.0095 45/126 [=========>....................] - ETA: 0s - loss: 1.5498e-04 - mean_absolute_error: 0.0093 67/126 [==============>...............] - ETA: 0s - loss: 1.5442e-04 - mean_absolute_error: 0.0094 89/126 [====================>.........] - ETA: 0s - loss: 1.5321e-04 - mean_absolute_error: 0.0094110/126 [=========================>....] - ETA: 0s - loss: 1.4540e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.5131e-04 - mean_absolute_error: 0.0093 - val_loss: 3.1287e-04 - val_mean_absolute_error: 0.0163
Epoch 45/100
1/126 [..............................] - ETA: 0s - loss: 4.4745e-04 - mean_absolute_error: 0.0191 23/126 [====>.........................] - ETA: 0s - loss: 3.3682e-04 - mean_absolute_error: 0.0142 45/126 [=========>....................] - ETA: 0s - loss: 2.4520e-04 - mean_absolute_error: 0.0116 67/126 [==============>...............] - ETA: 0s - loss: 2.1687e-04 - mean_absolute_error: 0.0110 90/126 [====================>.........] - ETA: 0s - loss: 2.0040e-04 - mean_absolute_error: 0.0107112/126 [=========================>....] - ETA: 0s - loss: 1.8753e-04 - mean_absolute_error: 0.0103126/126 [==============================] - 0s 3ms/step - loss: 1.7999e-04 - mean_absolute_error: 0.0101 - val_loss: 5.9871e-05 - val_mean_absolute_error: 0.0062
Epoch 46/100
1/126 [..............................] - ETA: 0s - loss: 1.2251e-04 - mean_absolute_error: 0.0087 23/126 [====>.........................] - ETA: 0s - loss: 1.4774e-04 - mean_absolute_error: 0.0093 45/126 [=========>....................] - ETA: 0s - loss: 1.7101e-04 - mean_absolute_error: 0.0098 67/126 [==============>...............] - ETA: 0s - loss: 1.6631e-04 - mean_absolute_error: 0.0097 88/126 [===================>..........] - ETA: 0s - loss: 1.8657e-04 - mean_absolute_error: 0.0103110/126 [=========================>....] - ETA: 0s - loss: 1.7892e-04 - mean_absolute_error: 0.0101126/126 [==============================] - 0s 3ms/step - loss: 1.7369e-04 - mean_absolute_error: 0.0100 - val_loss: 6.3912e-05 - val_mean_absolute_error: 0.0065
Epoch 47/100
1/126 [..............................] - ETA: 0s - loss: 1.1178e-04 - mean_absolute_error: 0.0080 23/126 [====>.........................] - ETA: 0s - loss: 1.3471e-04 - mean_absolute_error: 0.0088 45/126 [=========>....................] - ETA: 0s - loss: 1.4530e-04 - mean_absolute_error: 0.0088 67/126 [==============>...............] - ETA: 0s - loss: 1.4039e-04 - mean_absolute_error: 0.0088 89/126 [====================>.........] - ETA: 0s - loss: 1.4084e-04 - mean_absolute_error: 0.0089112/126 [=========================>....] - ETA: 0s - loss: 1.3841e-04 - mean_absolute_error: 0.0089126/126 [==============================] - 0s 3ms/step - loss: 1.4146e-04 - mean_absolute_error: 0.0089 - val_loss: 9.5510e-05 - val_mean_absolute_error: 0.0080
Epoch 48/100
1/126 [..............................] - ETA: 0s - loss: 2.5203e-04 - mean_absolute_error: 0.0126 23/126 [====>.........................] - ETA: 0s - loss: 1.8148e-04 - mean_absolute_error: 0.0093 45/126 [=========>....................] - ETA: 0s - loss: 1.6250e-04 - mean_absolute_error: 0.0092 67/126 [==============>...............] - ETA: 0s - loss: 1.4451e-04 - mean_absolute_error: 0.0089 89/126 [====================>.........] - ETA: 0s - loss: 1.4520e-04 - mean_absolute_error: 0.0089111/126 [=========================>....] - ETA: 0s - loss: 1.5069e-04 - mean_absolute_error: 0.0091126/126 [==============================] - 0s 3ms/step - loss: 1.5379e-04 - mean_absolute_error: 0.0093 - val_loss: 6.8592e-05 - val_mean_absolute_error: 0.0067
Epoch 49/100
1/126 [..............................] - ETA: 0s - loss: 7.0984e-05 - mean_absolute_error: 0.0062 23/126 [====>.........................] - ETA: 0s - loss: 2.0312e-04 - mean_absolute_error: 0.0107 45/126 [=========>....................] - ETA: 0s - loss: 1.8687e-04 - mean_absolute_error: 0.0105 67/126 [==============>...............] - ETA: 0s - loss: 1.7050e-04 - mean_absolute_error: 0.0100 89/126 [====================>.........] - ETA: 0s - loss: 1.6362e-04 - mean_absolute_error: 0.0096109/126 [========================>.....] - ETA: 0s - loss: 1.5990e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.6224e-04 - mean_absolute_error: 0.0097 - val_loss: 8.1884e-05 - val_mean_absolute_error: 0.0074
Epoch 50/100
1/126 [..............................] - ETA: 0s - loss: 2.9508e-04 - mean_absolute_error: 0.0140 23/126 [====>.........................] - ETA: 0s - loss: 1.7374e-04 - mean_absolute_error: 0.0101 45/126 [=========>....................] - ETA: 0s - loss: 1.7777e-04 - mean_absolute_error: 0.0101 67/126 [==============>...............] - ETA: 0s - loss: 1.7560e-04 - mean_absolute_error: 0.0099 89/126 [====================>.........] - ETA: 0s - loss: 1.6923e-04 - mean_absolute_error: 0.0097110/126 [=========================>....] - ETA: 0s - loss: 1.6667e-04 - mean_absolute_error: 0.0098126/126 [==============================] - 0s 3ms/step - loss: 1.6498e-04 - mean_absolute_error: 0.0097 - val_loss: 5.7456e-05 - val_mean_absolute_error: 0.0060
Epoch 51/100
1/126 [..............................] - ETA: 0s - loss: 1.1639e-04 - mean_absolute_error: 0.0086 23/126 [====>.........................] - ETA: 0s - loss: 1.1823e-04 - mean_absolute_error: 0.0084 45/126 [=========>....................] - ETA: 0s - loss: 1.5174e-04 - mean_absolute_error: 0.0090 67/126 [==============>...............] - ETA: 0s - loss: 1.4990e-04 - mean_absolute_error: 0.0091 89/126 [====================>.........] - ETA: 0s - loss: 1.4329e-04 - mean_absolute_error: 0.0089111/126 [=========================>....] - ETA: 0s - loss: 1.4146e-04 - mean_absolute_error: 0.0089126/126 [==============================] - 0s 3ms/step - loss: 1.4424e-04 - mean_absolute_error: 0.0090 - val_loss: 5.8498e-05 - val_mean_absolute_error: 0.0061
Epoch 52/100
1/126 [..............................] - ETA: 0s - loss: 1.8908e-04 - mean_absolute_error: 0.0096 22/126 [====>.........................] - ETA: 0s - loss: 1.4164e-04 - mean_absolute_error: 0.0085 45/126 [=========>....................] - ETA: 0s - loss: 1.6367e-04 - mean_absolute_error: 0.0096 67/126 [==============>...............] - ETA: 0s - loss: 1.6097e-04 - mean_absolute_error: 0.0097 89/126 [====================>.........] - ETA: 0s - loss: 1.6260e-04 - mean_absolute_error: 0.0095111/126 [=========================>....] - ETA: 0s - loss: 1.5702e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5824e-04 - mean_absolute_error: 0.0095 - val_loss: 8.8558e-05 - val_mean_absolute_error: 0.0078
Epoch 53/100
1/126 [..............................] - ETA: 0s - loss: 1.6690e-04 - mean_absolute_error: 0.0103 24/126 [====>.........................] - ETA: 0s - loss: 1.3083e-04 - mean_absolute_error: 0.0087 46/126 [=========>....................] - ETA: 0s - loss: 1.5033e-04 - mean_absolute_error: 0.0093 68/126 [===============>..............] - ETA: 0s - loss: 1.5010e-04 - mean_absolute_error: 0.0093 89/126 [====================>.........] - ETA: 0s - loss: 1.4830e-04 - mean_absolute_error: 0.0094111/126 [=========================>....] - ETA: 0s - loss: 1.6688e-04 - mean_absolute_error: 0.0099126/126 [==============================] - 0s 3ms/step - loss: 1.6830e-04 - mean_absolute_error: 0.0098 - val_loss: 4.7316e-05 - val_mean_absolute_error: 0.0052
Epoch 54/100
1/126 [..............................] - ETA: 0s - loss: 1.7751e-04 - mean_absolute_error: 0.0095 23/126 [====>.........................] - ETA: 0s - loss: 1.4623e-04 - mean_absolute_error: 0.0096 45/126 [=========>....................] - ETA: 0s - loss: 1.6088e-04 - mean_absolute_error: 0.0099 67/126 [==============>...............] - ETA: 0s - loss: 1.5652e-04 - mean_absolute_error: 0.0097 89/126 [====================>.........] - ETA: 0s - loss: 1.6184e-04 - mean_absolute_error: 0.0097111/126 [=========================>....] - ETA: 0s - loss: 1.7604e-04 - mean_absolute_error: 0.0101126/126 [==============================] - 0s 3ms/step - loss: 1.7246e-04 - mean_absolute_error: 0.0100 - val_loss: 1.2413e-04 - val_mean_absolute_error: 0.0094
Epoch 55/100
1/126 [..............................] - ETA: 0s - loss: 2.8713e-04 - mean_absolute_error: 0.0143 23/126 [====>.........................] - ETA: 0s - loss: 1.7877e-04 - mean_absolute_error: 0.0106 42/126 [=========>....................] - ETA: 0s - loss: 1.6736e-04 - mean_absolute_error: 0.0102 62/126 [=============>................] - ETA: 0s - loss: 1.7250e-04 - mean_absolute_error: 0.0102 84/126 [===================>..........] - ETA: 0s - loss: 1.7027e-04 - mean_absolute_error: 0.0099106/126 [========================>.....] - ETA: 0s - loss: 1.6765e-04 - mean_absolute_error: 0.0099126/126 [==============================] - 0s 3ms/step - loss: 1.7552e-04 - mean_absolute_error: 0.0102 - val_loss: 7.4861e-05 - val_mean_absolute_error: 0.0071
Epoch 56/100
1/126 [..............................] - ETA: 0s - loss: 1.5125e-04 - mean_absolute_error: 0.0099 23/126 [====>.........................] - ETA: 0s - loss: 1.6571e-04 - mean_absolute_error: 0.0103 45/126 [=========>....................] - ETA: 0s - loss: 1.3859e-04 - mean_absolute_error: 0.0092 66/126 [==============>...............] - ETA: 0s - loss: 1.4258e-04 - mean_absolute_error: 0.0092 87/126 [===================>..........] - ETA: 0s - loss: 1.5327e-04 - mean_absolute_error: 0.0092109/126 [========================>.....] - ETA: 0s - loss: 1.5412e-04 - mean_absolute_error: 0.0093126/126 [==============================] - 0s 3ms/step - loss: 1.5416e-04 - mean_absolute_error: 0.0094 - val_loss: 4.7964e-05 - val_mean_absolute_error: 0.0054
Epoch 57/100
1/126 [..............................] - ETA: 0s - loss: 1.6057e-04 - mean_absolute_error: 0.0090 23/126 [====>.........................] - ETA: 0s - loss: 1.3816e-04 - mean_absolute_error: 0.0090 45/126 [=========>....................] - ETA: 0s - loss: 1.3345e-04 - mean_absolute_error: 0.0087 67/126 [==============>...............] - ETA: 0s - loss: 1.3494e-04 - mean_absolute_error: 0.0088 88/126 [===================>..........] - ETA: 0s - loss: 1.3995e-04 - mean_absolute_error: 0.0089109/126 [========================>.....] - ETA: 0s - loss: 1.4028e-04 - mean_absolute_error: 0.0089126/126 [==============================] - 0s 3ms/step - loss: 1.4561e-04 - mean_absolute_error: 0.0090 - val_loss: 6.0135e-05 - val_mean_absolute_error: 0.0062
Epoch 58/100
1/126 [..............................] - ETA: 0s - loss: 7.8126e-05 - mean_absolute_error: 0.0072 24/126 [====>.........................] - ETA: 0s - loss: 1.4701e-04 - mean_absolute_error: 0.0093 45/126 [=========>....................] - ETA: 0s - loss: 1.4855e-04 - mean_absolute_error: 0.0095 66/126 [==============>...............] - ETA: 0s - loss: 1.3916e-04 - mean_absolute_error: 0.0092 87/126 [===================>..........] - ETA: 0s - loss: 1.4838e-04 - mean_absolute_error: 0.0093109/126 [========================>.....] - ETA: 0s - loss: 1.4111e-04 - mean_absolute_error: 0.0090126/126 [==============================] - 0s 3ms/step - loss: 1.4493e-04 - mean_absolute_error: 0.0091 - val_loss: 4.7850e-05 - val_mean_absolute_error: 0.0054
Epoch 59/100
1/126 [..............................] - ETA: 0s - loss: 5.2196e-05 - mean_absolute_error: 0.0057 23/126 [====>.........................] - ETA: 0s - loss: 1.2088e-04 - mean_absolute_error: 0.0084 45/126 [=========>....................] - ETA: 0s - loss: 1.3116e-04 - mean_absolute_error: 0.0087 67/126 [==============>...............] - ETA: 0s - loss: 1.5518e-04 - mean_absolute_error: 0.0094 88/126 [===================>..........] - ETA: 0s - loss: 1.4918e-04 - mean_absolute_error: 0.0093110/126 [=========================>....] - ETA: 0s - loss: 1.5504e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5379e-04 - mean_absolute_error: 0.0093 - val_loss: 7.5561e-05 - val_mean_absolute_error: 0.0071
Epoch 60/100
1/126 [..............................] - ETA: 0s - loss: 1.7253e-04 - mean_absolute_error: 0.0110 23/126 [====>.........................] - ETA: 0s - loss: 1.5088e-04 - mean_absolute_error: 0.0088 45/126 [=========>....................] - ETA: 0s - loss: 1.4597e-04 - mean_absolute_error: 0.0089 68/126 [===============>..............] - ETA: 0s - loss: 1.4659e-04 - mean_absolute_error: 0.0091 90/126 [====================>.........] - ETA: 0s - loss: 1.5175e-04 - mean_absolute_error: 0.0092111/126 [=========================>....] - ETA: 0s - loss: 1.4903e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.5603e-04 - mean_absolute_error: 0.0094 - val_loss: 1.1373e-04 - val_mean_absolute_error: 0.0091
Epoch 61/100
1/126 [..............................] - ETA: 0s - loss: 2.0162e-04 - mean_absolute_error: 0.0112 23/126 [====>.........................] - ETA: 0s - loss: 2.4627e-04 - mean_absolute_error: 0.0114 45/126 [=========>....................] - ETA: 0s - loss: 2.0165e-04 - mean_absolute_error: 0.0105 67/126 [==============>...............] - ETA: 0s - loss: 1.8419e-04 - mean_absolute_error: 0.0101 89/126 [====================>.........] - ETA: 0s - loss: 1.7481e-04 - mean_absolute_error: 0.0099110/126 [=========================>....] - ETA: 0s - loss: 1.6697e-04 - mean_absolute_error: 0.0097126/126 [==============================] - 0s 3ms/step - loss: 1.6225e-04 - mean_absolute_error: 0.0096 - val_loss: 4.6182e-05 - val_mean_absolute_error: 0.0052
Epoch 62/100
1/126 [..............................] - ETA: 0s - loss: 1.4363e-04 - mean_absolute_error: 0.0082 23/126 [====>.........................] - ETA: 0s - loss: 1.1505e-04 - mean_absolute_error: 0.0083 45/126 [=========>....................] - ETA: 0s - loss: 1.3471e-04 - mean_absolute_error: 0.0086 65/126 [==============>...............] - ETA: 0s - loss: 1.3987e-04 - mean_absolute_error: 0.0090 87/126 [===================>..........] - ETA: 0s - loss: 1.4766e-04 - mean_absolute_error: 0.0090109/126 [========================>.....] - ETA: 0s - loss: 1.5254e-04 - mean_absolute_error: 0.0093126/126 [==============================] - 0s 3ms/step - loss: 1.5309e-04 - mean_absolute_error: 0.0093 - val_loss: 4.7382e-05 - val_mean_absolute_error: 0.0054
Epoch 63/100
1/126 [..............................] - ETA: 0s - loss: 1.0741e-04 - mean_absolute_error: 0.0079 24/126 [====>.........................] - ETA: 0s - loss: 1.2049e-04 - mean_absolute_error: 0.0083 46/126 [=========>....................] - ETA: 0s - loss: 1.5513e-04 - mean_absolute_error: 0.0090 68/126 [===============>..............] - ETA: 0s - loss: 1.7746e-04 - mean_absolute_error: 0.0099 90/126 [====================>.........] - ETA: 0s - loss: 1.7419e-04 - mean_absolute_error: 0.0099111/126 [=========================>....] - ETA: 0s - loss: 1.6842e-04 - mean_absolute_error: 0.0097126/126 [==============================] - 0s 3ms/step - loss: 1.6466e-04 - mean_absolute_error: 0.0097 - val_loss: 6.1684e-05 - val_mean_absolute_error: 0.0063
Epoch 64/100
1/126 [..............................] - ETA: 0s - loss: 1.7949e-04 - mean_absolute_error: 0.0100 23/126 [====>.........................] - ETA: 0s - loss: 1.7108e-04 - mean_absolute_error: 0.0102 45/126 [=========>....................] - ETA: 0s - loss: 1.6712e-04 - mean_absolute_error: 0.0102 67/126 [==============>...............] - ETA: 0s - loss: 1.5959e-04 - mean_absolute_error: 0.0099 89/126 [====================>.........] - ETA: 0s - loss: 1.6163e-04 - mean_absolute_error: 0.0096111/126 [=========================>....] - ETA: 0s - loss: 1.5659e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.5455e-04 - mean_absolute_error: 0.0094 - val_loss: 4.8549e-05 - val_mean_absolute_error: 0.0055
Epoch 65/100
1/126 [..............................] - ETA: 0s - loss: 9.3439e-05 - mean_absolute_error: 0.0066 23/126 [====>.........................] - ETA: 0s - loss: 1.5452e-04 - mean_absolute_error: 0.0096 45/126 [=========>....................] - ETA: 0s - loss: 1.6034e-04 - mean_absolute_error: 0.0095 67/126 [==============>...............] - ETA: 0s - loss: 1.4895e-04 - mean_absolute_error: 0.0092 89/126 [====================>.........] - ETA: 0s - loss: 1.4279e-04 - mean_absolute_error: 0.0090111/126 [=========================>....] - ETA: 0s - loss: 1.4729e-04 - mean_absolute_error: 0.0091126/126 [==============================] - 0s 3ms/step - loss: 1.4971e-04 - mean_absolute_error: 0.0092 - val_loss: 1.3334e-04 - val_mean_absolute_error: 0.0099
Epoch 66/100
1/126 [..............................] - ETA: 0s - loss: 3.1997e-04 - mean_absolute_error: 0.0149 19/126 [===>..........................] - ETA: 0s - loss: 2.3397e-04 - mean_absolute_error: 0.0125 41/126 [========>.....................] - ETA: 0s - loss: 2.0542e-04 - mean_absolute_error: 0.0111 63/126 [==============>...............] - ETA: 0s - loss: 1.8182e-04 - mean_absolute_error: 0.0104 85/126 [===================>..........] - ETA: 0s - loss: 1.6610e-04 - mean_absolute_error: 0.0098107/126 [========================>.....] - ETA: 0s - loss: 1.5592e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.5758e-04 - mean_absolute_error: 0.0095 - val_loss: 4.5939e-05 - val_mean_absolute_error: 0.0052
Epoch 67/100
1/126 [..............................] - ETA: 0s - loss: 7.7973e-05 - mean_absolute_error: 0.0062 23/126 [====>.........................] - ETA: 0s - loss: 1.4451e-04 - mean_absolute_error: 0.0087 45/126 [=========>....................] - ETA: 0s - loss: 1.4768e-04 - mean_absolute_error: 0.0090 67/126 [==============>...............] - ETA: 0s - loss: 1.4571e-04 - mean_absolute_error: 0.0091 88/126 [===================>..........] - ETA: 0s - loss: 1.5014e-04 - mean_absolute_error: 0.0091109/126 [========================>.....] - ETA: 0s - loss: 1.4921e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.4358e-04 - mean_absolute_error: 0.0090 - val_loss: 5.0663e-05 - val_mean_absolute_error: 0.0057
Epoch 68/100
1/126 [..............................] - ETA: 0s - loss: 6.8013e-05 - mean_absolute_error: 0.0062 23/126 [====>.........................] - ETA: 0s - loss: 1.1630e-04 - mean_absolute_error: 0.0084 45/126 [=========>....................] - ETA: 0s - loss: 1.3336e-04 - mean_absolute_error: 0.0087 67/126 [==============>...............] - ETA: 0s - loss: 1.2761e-04 - mean_absolute_error: 0.0085 89/126 [====================>.........] - ETA: 0s - loss: 1.2760e-04 - mean_absolute_error: 0.0085111/126 [=========================>....] - ETA: 0s - loss: 1.3118e-04 - mean_absolute_error: 0.0086126/126 [==============================] - 0s 3ms/step - loss: 1.3541e-04 - mean_absolute_error: 0.0086 - val_loss: 7.5739e-05 - val_mean_absolute_error: 0.0072
Epoch 69/100
1/126 [..............................] - ETA: 0s - loss: 1.2138e-04 - mean_absolute_error: 0.0089 24/126 [====>.........................] - ETA: 0s - loss: 1.3653e-04 - mean_absolute_error: 0.0089 47/126 [==========>...................] - ETA: 0s - loss: 1.2644e-04 - mean_absolute_error: 0.0085 70/126 [===============>..............] - ETA: 0s - loss: 1.5165e-04 - mean_absolute_error: 0.0090 92/126 [====================>.........] - ETA: 0s - loss: 1.4748e-04 - mean_absolute_error: 0.0090114/126 [==========================>...] - ETA: 0s - loss: 1.5246e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.5045e-04 - mean_absolute_error: 0.0092 - val_loss: 8.6990e-05 - val_mean_absolute_error: 0.0077
Epoch 70/100
1/126 [..............................] - ETA: 0s - loss: 2.5458e-04 - mean_absolute_error: 0.0113 23/126 [====>.........................] - ETA: 0s - loss: 1.8911e-04 - mean_absolute_error: 0.0098 45/126 [=========>....................] - ETA: 0s - loss: 1.6276e-04 - mean_absolute_error: 0.0094 67/126 [==============>...............] - ETA: 0s - loss: 1.5805e-04 - mean_absolute_error: 0.0094 90/126 [====================>.........] - ETA: 0s - loss: 1.7703e-04 - mean_absolute_error: 0.0101112/126 [=========================>....] - ETA: 0s - loss: 1.6850e-04 - mean_absolute_error: 0.0098126/126 [==============================] - 0s 3ms/step - loss: 1.6463e-04 - mean_absolute_error: 0.0097 - val_loss: 1.2774e-04 - val_mean_absolute_error: 0.0097
Epoch 71/100
1/126 [..............................] - ETA: 0s - loss: 1.6797e-04 - mean_absolute_error: 0.0102 23/126 [====>.........................] - ETA: 0s - loss: 1.6162e-04 - mean_absolute_error: 0.0093 45/126 [=========>....................] - ETA: 0s - loss: 1.5191e-04 - mean_absolute_error: 0.0091 67/126 [==============>...............] - ETA: 0s - loss: 1.5013e-04 - mean_absolute_error: 0.0089 89/126 [====================>.........] - ETA: 0s - loss: 1.4094e-04 - mean_absolute_error: 0.0087111/126 [=========================>....] - ETA: 0s - loss: 1.3473e-04 - mean_absolute_error: 0.0086126/126 [==============================] - 0s 3ms/step - loss: 1.3265e-04 - mean_absolute_error: 0.0085 - val_loss: 4.7863e-05 - val_mean_absolute_error: 0.0055
Epoch 72/100
1/126 [..............................] - ETA: 0s - loss: 1.4089e-04 - mean_absolute_error: 0.0094 24/126 [====>.........................] - ETA: 0s - loss: 1.7123e-04 - mean_absolute_error: 0.0102 47/126 [==========>...................] - ETA: 0s - loss: 1.6631e-04 - mean_absolute_error: 0.0100 69/126 [===============>..............] - ETA: 0s - loss: 1.5944e-04 - mean_absolute_error: 0.0096 91/126 [====================>.........] - ETA: 0s - loss: 1.5130e-04 - mean_absolute_error: 0.0093113/126 [=========================>....] - ETA: 0s - loss: 1.5949e-04 - mean_absolute_error: 0.0095126/126 [==============================] - 0s 3ms/step - loss: 1.6087e-04 - mean_absolute_error: 0.0096 - val_loss: 6.6773e-05 - val_mean_absolute_error: 0.0067
Epoch 73/100
1/126 [..............................] - ETA: 0s - loss: 1.1757e-04 - mean_absolute_error: 0.0087 23/126 [====>.........................] - ETA: 0s - loss: 1.5368e-04 - mean_absolute_error: 0.0094 46/126 [=========>....................] - ETA: 0s - loss: 1.4508e-04 - mean_absolute_error: 0.0091 67/126 [==============>...............] - ETA: 0s - loss: 1.3681e-04 - mean_absolute_error: 0.0088 89/126 [====================>.........] - ETA: 0s - loss: 1.4280e-04 - mean_absolute_error: 0.0089111/126 [=========================>....] - ETA: 0s - loss: 1.4197e-04 - mean_absolute_error: 0.0088126/126 [==============================] - 0s 3ms/step - loss: 1.4034e-04 - mean_absolute_error: 0.0088 - val_loss: 1.2608e-04 - val_mean_absolute_error: 0.0095
Epoch 74/100
1/126 [..............................] - ETA: 0s - loss: 2.6250e-04 - mean_absolute_error: 0.0140 23/126 [====>.........................] - ETA: 0s - loss: 1.8336e-04 - mean_absolute_error: 0.0104 44/126 [=========>....................] - ETA: 0s - loss: 1.7594e-04 - mean_absolute_error: 0.0100 66/126 [==============>...............] - ETA: 0s - loss: 1.7571e-04 - mean_absolute_error: 0.0100 88/126 [===================>..........] - ETA: 0s - loss: 1.6235e-04 - mean_absolute_error: 0.0097110/126 [=========================>....] - ETA: 0s - loss: 1.5923e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5661e-04 - mean_absolute_error: 0.0094 - val_loss: 8.0961e-05 - val_mean_absolute_error: 0.0074
Epoch 75/100
1/126 [..............................] - ETA: 0s - loss: 7.0830e-05 - mean_absolute_error: 0.0066 24/126 [====>.........................] - ETA: 0s - loss: 1.7482e-04 - mean_absolute_error: 0.0096 47/126 [==========>...................] - ETA: 0s - loss: 1.8071e-04 - mean_absolute_error: 0.0101 70/126 [===============>..............] - ETA: 0s - loss: 1.5769e-04 - mean_absolute_error: 0.0094 92/126 [====================>.........] - ETA: 0s - loss: 1.5619e-04 - mean_absolute_error: 0.0093114/126 [==========================>...] - ETA: 0s - loss: 1.5483e-04 - mean_absolute_error: 0.0093126/126 [==============================] - 0s 3ms/step - loss: 1.5358e-04 - mean_absolute_error: 0.0093 - val_loss: 5.1733e-05 - val_mean_absolute_error: 0.0057
Epoch 76/100
1/126 [..............................] - ETA: 0s - loss: 8.0646e-05 - mean_absolute_error: 0.0070 24/126 [====>.........................] - ETA: 0s - loss: 1.3142e-04 - mean_absolute_error: 0.0087 46/126 [=========>....................] - ETA: 0s - loss: 1.2458e-04 - mean_absolute_error: 0.0085 65/126 [==============>...............] - ETA: 0s - loss: 1.3195e-04 - mean_absolute_error: 0.0088 87/126 [===================>..........] - ETA: 0s - loss: 1.3114e-04 - mean_absolute_error: 0.0088109/126 [========================>.....] - ETA: 0s - loss: 1.3337e-04 - mean_absolute_error: 0.0088126/126 [==============================] - 0s 3ms/step - loss: 1.3561e-04 - mean_absolute_error: 0.0087 - val_loss: 6.5435e-05 - val_mean_absolute_error: 0.0066
Epoch 77/100
1/126 [..............................] - ETA: 0s - loss: 3.1392e-04 - mean_absolute_error: 0.0136 23/126 [====>.........................] - ETA: 0s - loss: 1.3053e-04 - mean_absolute_error: 0.0087 45/126 [=========>....................] - ETA: 0s - loss: 1.4645e-04 - mean_absolute_error: 0.0093 68/126 [===============>..............] - ETA: 0s - loss: 1.4789e-04 - mean_absolute_error: 0.0094 90/126 [====================>.........] - ETA: 0s - loss: 1.4952e-04 - mean_absolute_error: 0.0093112/126 [=========================>....] - ETA: 0s - loss: 1.4631e-04 - mean_absolute_error: 0.0093126/126 [==============================] - 0s 3ms/step - loss: 1.5139e-04 - mean_absolute_error: 0.0093 - val_loss: 1.2101e-04 - val_mean_absolute_error: 0.0093
Epoch 78/100
1/126 [..............................] - ETA: 0s - loss: 1.5927e-04 - mean_absolute_error: 0.0105 23/126 [====>.........................] - ETA: 0s - loss: 1.3388e-04 - mean_absolute_error: 0.0090 45/126 [=========>....................] - ETA: 0s - loss: 1.2730e-04 - mean_absolute_error: 0.0087 67/126 [==============>...............] - ETA: 0s - loss: 1.2638e-04 - mean_absolute_error: 0.0086 90/126 [====================>.........] - ETA: 0s - loss: 1.4649e-04 - mean_absolute_error: 0.0092113/126 [=========================>....] - ETA: 0s - loss: 1.4863e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.4627e-04 - mean_absolute_error: 0.0091 - val_loss: 5.1100e-05 - val_mean_absolute_error: 0.0057
Epoch 79/100
1/126 [..............................] - ETA: 0s - loss: 1.9565e-04 - mean_absolute_error: 0.0100 24/126 [====>.........................] - ETA: 0s - loss: 1.2482e-04 - mean_absolute_error: 0.0083 47/126 [==========>...................] - ETA: 0s - loss: 1.4521e-04 - mean_absolute_error: 0.0091 69/126 [===============>..............] - ETA: 0s - loss: 1.3406e-04 - mean_absolute_error: 0.0088 92/126 [====================>.........] - ETA: 0s - loss: 1.2987e-04 - mean_absolute_error: 0.0087114/126 [==========================>...] - ETA: 0s - loss: 1.3707e-04 - mean_absolute_error: 0.0087126/126 [==============================] - 0s 3ms/step - loss: 1.3671e-04 - mean_absolute_error: 0.0087 - val_loss: 7.6422e-05 - val_mean_absolute_error: 0.0072
Epoch 80/100
1/126 [..............................] - ETA: 0s - loss: 1.4927e-04 - mean_absolute_error: 0.0101 23/126 [====>.........................] - ETA: 0s - loss: 1.4562e-04 - mean_absolute_error: 0.0092 45/126 [=========>....................] - ETA: 0s - loss: 1.3167e-04 - mean_absolute_error: 0.0087 67/126 [==============>...............] - ETA: 0s - loss: 1.5495e-04 - mean_absolute_error: 0.0092 89/126 [====================>.........] - ETA: 0s - loss: 1.7293e-04 - mean_absolute_error: 0.0099111/126 [=========================>....] - ETA: 0s - loss: 1.7032e-04 - mean_absolute_error: 0.0099126/126 [==============================] - 0s 3ms/step - loss: 1.6699e-04 - mean_absolute_error: 0.0098 - val_loss: 5.1005e-05 - val_mean_absolute_error: 0.0056
Epoch 81/100
1/126 [..............................] - ETA: 0s - loss: 9.1869e-05 - mean_absolute_error: 0.0065 23/126 [====>.........................] - ETA: 0s - loss: 1.1229e-04 - mean_absolute_error: 0.0081 45/126 [=========>....................] - ETA: 0s - loss: 1.1330e-04 - mean_absolute_error: 0.0082 67/126 [==============>...............] - ETA: 0s - loss: 1.1452e-04 - mean_absolute_error: 0.0082 89/126 [====================>.........] - ETA: 0s - loss: 1.2191e-04 - mean_absolute_error: 0.0083111/126 [=========================>....] - ETA: 0s - loss: 1.2355e-04 - mean_absolute_error: 0.0084126/126 [==============================] - 0s 3ms/step - loss: 1.2627e-04 - mean_absolute_error: 0.0084 - val_loss: 4.3917e-05 - val_mean_absolute_error: 0.0051
Epoch 82/100
1/126 [..............................] - ETA: 0s - loss: 8.6206e-05 - mean_absolute_error: 0.0080 23/126 [====>.........................] - ETA: 0s - loss: 1.6667e-04 - mean_absolute_error: 0.0093 45/126 [=========>....................] - ETA: 0s - loss: 1.4763e-04 - mean_absolute_error: 0.0091 67/126 [==============>...............] - ETA: 0s - loss: 1.4539e-04 - mean_absolute_error: 0.0089 88/126 [===================>..........] - ETA: 0s - loss: 1.4055e-04 - mean_absolute_error: 0.0088110/126 [=========================>....] - ETA: 0s - loss: 1.3305e-04 - mean_absolute_error: 0.0086126/126 [==============================] - 0s 3ms/step - loss: 1.3048e-04 - mean_absolute_error: 0.0085 - val_loss: 4.4104e-05 - val_mean_absolute_error: 0.0051
Epoch 83/100
1/126 [..............................] - ETA: 0s - loss: 9.1937e-05 - mean_absolute_error: 0.0075 21/126 [====>.........................] - ETA: 0s - loss: 1.1768e-04 - mean_absolute_error: 0.0083 40/126 [========>.....................] - ETA: 0s - loss: 1.2434e-04 - mean_absolute_error: 0.0085 59/126 [=============>................] - ETA: 0s - loss: 1.3392e-04 - mean_absolute_error: 0.0089 77/126 [=================>............] - ETA: 0s - loss: 1.3855e-04 - mean_absolute_error: 0.0091 97/126 [======================>.......] - ETA: 0s - loss: 1.4135e-04 - mean_absolute_error: 0.0091116/126 [==========================>...] - ETA: 0s - loss: 1.4218e-04 - mean_absolute_error: 0.0090126/126 [==============================] - 0s 3ms/step - loss: 1.4126e-04 - mean_absolute_error: 0.0090 - val_loss: 4.4395e-05 - val_mean_absolute_error: 0.0052
Epoch 84/100
1/126 [..............................] - ETA: 0s - loss: 9.8733e-05 - mean_absolute_error: 0.0073 23/126 [====>.........................] - ETA: 0s - loss: 1.3614e-04 - mean_absolute_error: 0.0085 44/126 [=========>....................] - ETA: 0s - loss: 1.3131e-04 - mean_absolute_error: 0.0085 66/126 [==============>...............] - ETA: 0s - loss: 1.3110e-04 - mean_absolute_error: 0.0086 88/126 [===================>..........] - ETA: 0s - loss: 1.4055e-04 - mean_absolute_error: 0.0087111/126 [=========================>....] - ETA: 0s - loss: 1.3369e-04 - mean_absolute_error: 0.0086126/126 [==============================] - 0s 3ms/step - loss: 1.3272e-04 - mean_absolute_error: 0.0086 - val_loss: 7.9347e-05 - val_mean_absolute_error: 0.0074
Epoch 85/100
1/126 [..............................] - ETA: 0s - loss: 1.9096e-04 - mean_absolute_error: 0.0118 24/126 [====>.........................] - ETA: 0s - loss: 1.6461e-04 - mean_absolute_error: 0.0099 46/126 [=========>....................] - ETA: 0s - loss: 1.9055e-04 - mean_absolute_error: 0.0106 68/126 [===============>..............] - ETA: 0s - loss: 1.7349e-04 - mean_absolute_error: 0.0101 90/126 [====================>.........] - ETA: 0s - loss: 1.6022e-04 - mean_absolute_error: 0.0097112/126 [=========================>....] - ETA: 0s - loss: 1.5528e-04 - mean_absolute_error: 0.0094126/126 [==============================] - 0s 3ms/step - loss: 1.5024e-04 - mean_absolute_error: 0.0093 - val_loss: 4.5659e-05 - val_mean_absolute_error: 0.0053
Epoch 86/100
1/126 [..............................] - ETA: 0s - loss: 9.2694e-05 - mean_absolute_error: 0.0082 23/126 [====>.........................] - ETA: 0s - loss: 1.1869e-04 - mean_absolute_error: 0.0083 44/126 [=========>....................] - ETA: 0s - loss: 1.2593e-04 - mean_absolute_error: 0.0082 66/126 [==============>...............] - ETA: 0s - loss: 1.2080e-04 - mean_absolute_error: 0.0082 88/126 [===================>..........] - ETA: 0s - loss: 1.2655e-04 - mean_absolute_error: 0.0084110/126 [=========================>....] - ETA: 0s - loss: 1.3537e-04 - mean_absolute_error: 0.0088126/126 [==============================] - 0s 3ms/step - loss: 1.4308e-04 - mean_absolute_error: 0.0090 - val_loss: 6.7774e-05 - val_mean_absolute_error: 0.0067
Epoch 87/100
1/126 [..............................] - ETA: 0s - loss: 1.5835e-04 - mean_absolute_error: 0.0093 23/126 [====>.........................] - ETA: 0s - loss: 1.2236e-04 - mean_absolute_error: 0.0086 45/126 [=========>....................] - ETA: 0s - loss: 1.3039e-04 - mean_absolute_error: 0.0088 68/126 [===============>..............] - ETA: 0s - loss: 1.3097e-04 - mean_absolute_error: 0.0087 90/126 [====================>.........] - ETA: 0s - loss: 1.3330e-04 - mean_absolute_error: 0.0087111/126 [=========================>....] - ETA: 0s - loss: 1.3871e-04 - mean_absolute_error: 0.0089126/126 [==============================] - 0s 3ms/step - loss: 1.3742e-04 - mean_absolute_error: 0.0089 - val_loss: 4.6340e-05 - val_mean_absolute_error: 0.0053
Epoch 88/100
1/126 [..............................] - ETA: 0s - loss: 1.0651e-04 - mean_absolute_error: 0.0077 23/126 [====>.........................] - ETA: 0s - loss: 1.3949e-04 - mean_absolute_error: 0.0085 45/126 [=========>....................] - ETA: 0s - loss: 1.2322e-04 - mean_absolute_error: 0.0082 67/126 [==============>...............] - ETA: 0s - loss: 1.2258e-04 - mean_absolute_error: 0.0083 89/126 [====================>.........] - ETA: 0s - loss: 1.2326e-04 - mean_absolute_error: 0.0082111/126 [=========================>....] - ETA: 0s - loss: 1.1888e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1926e-04 - mean_absolute_error: 0.0081 - val_loss: 4.6956e-05 - val_mean_absolute_error: 0.0054
Epoch 89/100
1/126 [..............................] - ETA: 0s - loss: 1.5306e-04 - mean_absolute_error: 0.0087 23/126 [====>.........................] - ETA: 0s - loss: 1.3493e-04 - mean_absolute_error: 0.0090 45/126 [=========>....................] - ETA: 0s - loss: 1.3740e-04 - mean_absolute_error: 0.0090 67/126 [==============>...............] - ETA: 0s - loss: 1.3552e-04 - mean_absolute_error: 0.0089 90/126 [====================>.........] - ETA: 0s - loss: 1.2987e-04 - mean_absolute_error: 0.0087112/126 [=========================>....] - ETA: 0s - loss: 1.2994e-04 - mean_absolute_error: 0.0087126/126 [==============================] - 0s 3ms/step - loss: 1.3427e-04 - mean_absolute_error: 0.0087 - val_loss: 1.0344e-04 - val_mean_absolute_error: 0.0086
Epoch 90/100
1/126 [..............................] - ETA: 0s - loss: 1.3231e-04 - mean_absolute_error: 0.0095 21/126 [====>.........................] - ETA: 0s - loss: 1.7092e-04 - mean_absolute_error: 0.0102 43/126 [=========>....................] - ETA: 0s - loss: 1.4629e-04 - mean_absolute_error: 0.0093 65/126 [==============>...............] - ETA: 0s - loss: 1.4500e-04 - mean_absolute_error: 0.0092 87/126 [===================>..........] - ETA: 0s - loss: 1.3714e-04 - mean_absolute_error: 0.0090109/126 [========================>.....] - ETA: 0s - loss: 1.3336e-04 - mean_absolute_error: 0.0088126/126 [==============================] - 0s 3ms/step - loss: 1.4009e-04 - mean_absolute_error: 0.0090 - val_loss: 4.7824e-05 - val_mean_absolute_error: 0.0055
Epoch 91/100
1/126 [..............................] - ETA: 0s - loss: 1.2895e-04 - mean_absolute_error: 0.0097 24/126 [====>.........................] - ETA: 0s - loss: 1.2663e-04 - mean_absolute_error: 0.0088 45/126 [=========>....................] - ETA: 0s - loss: 1.3641e-04 - mean_absolute_error: 0.0091 67/126 [==============>...............] - ETA: 0s - loss: 1.8886e-04 - mean_absolute_error: 0.0103 90/126 [====================>.........] - ETA: 0s - loss: 1.8509e-04 - mean_absolute_error: 0.0104112/126 [=========================>....] - ETA: 0s - loss: 1.7373e-04 - mean_absolute_error: 0.0100126/126 [==============================] - 0s 3ms/step - loss: 1.6864e-04 - mean_absolute_error: 0.0099 - val_loss: 4.1948e-05 - val_mean_absolute_error: 0.0048
Epoch 92/100
1/126 [..............................] - ETA: 0s - loss: 1.3992e-04 - mean_absolute_error: 0.0087 23/126 [====>.........................] - ETA: 0s - loss: 1.4518e-04 - mean_absolute_error: 0.0095 45/126 [=========>....................] - ETA: 0s - loss: 1.5944e-04 - mean_absolute_error: 0.0096 67/126 [==============>...............] - ETA: 0s - loss: 1.4412e-04 - mean_absolute_error: 0.0091 89/126 [====================>.........] - ETA: 0s - loss: 1.4901e-04 - mean_absolute_error: 0.0092112/126 [=========================>....] - ETA: 0s - loss: 1.4188e-04 - mean_absolute_error: 0.0090126/126 [==============================] - 0s 3ms/step - loss: 1.3758e-04 - mean_absolute_error: 0.0089 - val_loss: 5.8066e-05 - val_mean_absolute_error: 0.0062
Epoch 93/100
1/126 [..............................] - ETA: 0s - loss: 1.5430e-04 - mean_absolute_error: 0.0101 24/126 [====>.........................] - ETA: 0s - loss: 1.8887e-04 - mean_absolute_error: 0.0107 46/126 [=========>....................] - ETA: 0s - loss: 1.8860e-04 - mean_absolute_error: 0.0103 69/126 [===============>..............] - ETA: 0s - loss: 1.8357e-04 - mean_absolute_error: 0.0104 92/126 [====================>.........] - ETA: 0s - loss: 1.6857e-04 - mean_absolute_error: 0.0100114/126 [==========================>...] - ETA: 0s - loss: 1.6208e-04 - mean_absolute_error: 0.0098126/126 [==============================] - 0s 3ms/step - loss: 1.5771e-04 - mean_absolute_error: 0.0097 - val_loss: 4.1720e-05 - val_mean_absolute_error: 0.0048
Epoch 94/100
1/126 [..............................] - ETA: 0s - loss: 7.3304e-05 - mean_absolute_error: 0.0063 23/126 [====>.........................] - ETA: 0s - loss: 1.0120e-04 - mean_absolute_error: 0.0077 45/126 [=========>....................] - ETA: 0s - loss: 1.5764e-04 - mean_absolute_error: 0.0092 68/126 [===============>..............] - ETA: 0s - loss: 1.7800e-04 - mean_absolute_error: 0.0100 90/126 [====================>.........] - ETA: 0s - loss: 1.6142e-04 - mean_absolute_error: 0.0095112/126 [=========================>....] - ETA: 0s - loss: 1.5218e-04 - mean_absolute_error: 0.0093126/126 [==============================] - 0s 3ms/step - loss: 1.4962e-04 - mean_absolute_error: 0.0092 - val_loss: 7.0274e-05 - val_mean_absolute_error: 0.0069
Epoch 95/100
1/126 [..............................] - ETA: 0s - loss: 8.8100e-05 - mean_absolute_error: 0.0075 23/126 [====>.........................] - ETA: 0s - loss: 1.2010e-04 - mean_absolute_error: 0.0081 45/126 [=========>....................] - ETA: 0s - loss: 1.1954e-04 - mean_absolute_error: 0.0082 68/126 [===============>..............] - ETA: 0s - loss: 1.1819e-04 - mean_absolute_error: 0.0080 90/126 [====================>.........] - ETA: 0s - loss: 1.2118e-04 - mean_absolute_error: 0.0081111/126 [=========================>....] - ETA: 0s - loss: 1.1878e-04 - mean_absolute_error: 0.0081126/126 [==============================] - 0s 3ms/step - loss: 1.1639e-04 - mean_absolute_error: 0.0080 - val_loss: 4.1304e-05 - val_mean_absolute_error: 0.0047
Epoch 96/100
1/126 [..............................] - ETA: 0s - loss: 1.1572e-04 - mean_absolute_error: 0.0076 23/126 [====>.........................] - ETA: 0s - loss: 1.6781e-04 - mean_absolute_error: 0.0101 45/126 [=========>....................] - ETA: 0s - loss: 1.5093e-04 - mean_absolute_error: 0.0096 67/126 [==============>...............] - ETA: 0s - loss: 1.4165e-04 - mean_absolute_error: 0.0093 89/126 [====================>.........] - ETA: 0s - loss: 1.3946e-04 - mean_absolute_error: 0.0090111/126 [=========================>....] - ETA: 0s - loss: 1.4073e-04 - mean_absolute_error: 0.0090126/126 [==============================] - 0s 3ms/step - loss: 1.3803e-04 - mean_absolute_error: 0.0089 - val_loss: 5.1025e-05 - val_mean_absolute_error: 0.0057
Epoch 97/100
1/126 [..............................] - ETA: 0s - loss: 1.0674e-04 - mean_absolute_error: 0.0081 24/126 [====>.........................] - ETA: 0s - loss: 1.4798e-04 - mean_absolute_error: 0.0093 47/126 [==========>...................] - ETA: 0s - loss: 1.5725e-04 - mean_absolute_error: 0.0096 69/126 [===============>..............] - ETA: 0s - loss: 1.4623e-04 - mean_absolute_error: 0.0093 91/126 [====================>.........] - ETA: 0s - loss: 1.5331e-04 - mean_absolute_error: 0.0095113/126 [=========================>....] - ETA: 0s - loss: 1.4501e-04 - mean_absolute_error: 0.0092126/126 [==============================] - 0s 3ms/step - loss: 1.4993e-04 - mean_absolute_error: 0.0092 - val_loss: 1.1050e-04 - val_mean_absolute_error: 0.0090
Epoch 98/100
1/126 [..............................] - ETA: 0s - loss: 1.0990e-04 - mean_absolute_error: 0.0086 22/126 [====>.........................] - ETA: 0s - loss: 1.5196e-04 - mean_absolute_error: 0.0097 44/126 [=========>....................] - ETA: 0s - loss: 1.4487e-04 - mean_absolute_error: 0.0090 66/126 [==============>...............] - ETA: 0s - loss: 1.3116e-04 - mean_absolute_error: 0.0086 88/126 [===================>..........] - ETA: 0s - loss: 1.3362e-04 - mean_absolute_error: 0.0086109/126 [========================>.....] - ETA: 0s - loss: 1.2630e-04 - mean_absolute_error: 0.0084126/126 [==============================] - 0s 3ms/step - loss: 1.2573e-04 - mean_absolute_error: 0.0084 - val_loss: 8.6220e-05 - val_mean_absolute_error: 0.0078
Epoch 99/100
1/126 [..............................] - ETA: 0s - loss: 1.3723e-04 - mean_absolute_error: 0.0088 23/126 [====>.........................] - ETA: 0s - loss: 1.1052e-04 - mean_absolute_error: 0.0081 45/126 [=========>....................] - ETA: 0s - loss: 1.1975e-04 - mean_absolute_error: 0.0080 67/126 [==============>...............] - ETA: 0s - loss: 1.2266e-04 - mean_absolute_error: 0.0082 89/126 [====================>.........] - ETA: 0s - loss: 1.2453e-04 - mean_absolute_error: 0.0084110/126 [=========================>....] - ETA: 0s - loss: 1.3358e-04 - mean_absolute_error: 0.0087126/126 [==============================] - 0s 3ms/step - loss: 1.3365e-04 - mean_absolute_error: 0.0087 - val_loss: 4.2007e-05 - val_mean_absolute_error: 0.0050
Epoch 100/100
1/126 [..............................] - ETA: 0s - loss: 1.6072e-04 - mean_absolute_error: 0.0078 22/126 [====>.........................] - ETA: 0s - loss: 1.0710e-04 - mean_absolute_error: 0.0078 44/126 [=========>....................] - ETA: 0s - loss: 1.1800e-04 - mean_absolute_error: 0.0081 67/126 [==============>...............] - ETA: 0s - loss: 1.1498e-04 - mean_absolute_error: 0.0080 89/126 [====================>.........] - ETA: 0s - loss: 1.1293e-04 - mean_absolute_error: 0.0080111/126 [=========================>....] - ETA: 0s - loss: 1.2401e-04 - mean_absolute_error: 0.0083126/126 [==============================] - 0s 3ms/step - loss: 1.2771e-04 - mean_absolute_error: 0.0084 - val_loss: 7.6854e-05 - val_mean_absolute_error: 0.0073
<keras.src.callbacks.History at 0x1b9b5631ad0>
After the training and fitting of the Machine Learning model for Switzerland, I tried to create visualizations comparing the model against the country’s training dataset, validation dataset, but most importantly the testing dataset (as shown below in the line graphs). Note that the darker and thicker blue lines represent the prediction model’s projections and the thinner red lines is the observed/gathered data.
```{python}
# Testing the Machine Learning Model prediction for Switzerland with the train,
# validation, and test sets
# Most important is the test set prediction as this tests the effectiveness
# of the Machine Learning model on data it has not seen before
switzerland_train_pred = switzerland_model.predict(X_switzerland_train).flatten()
plt.plot(dates_switzerland_train, switzerland_train_pred, linewidth=4)
plt.plot(dates_switzerland_train, y_switzerland_train, linewidth=1)
plt.legend(["Training Predictions", "Training Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Switzerland - Training Set Predictions vs. Observations")
plt.show()
switzerland_val_pred = switzerland_model.predict(X_switzerland_val).flatten()
plt.plot(dates_switzerland_val, switzerland_val_pred, linewidth=4)
plt.plot(dates_switzerland_val, y_switzerland_val, linewidth=1)
plt.legend(["Validation Predictions", "Validation Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Switzerland - Validation Set Predictions vs. Observations")
plt.show()
switzerland_test_pred = switzerland_model.predict(X_switzerland_test).flatten()
plt.plot(dates_switzerland_test, switzerland_test_pred, linewidth=4)
plt.plot(dates_switzerland_test, y_switzerland_test, linewidth=1)
plt.legend(["Testing Predictions", "Testing Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Switzerland - Testing Set Predictions vs. Observations")
plt.show()
``` 1/126 [..............................] - ETA: 44s 45/126 [=========>....................] - ETA: 0s 89/126 [====================>.........] - ETA: 0s126/126 [==============================] - 0s 1ms/step
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1/16 [>.............................] - ETA: 0s16/16 [==============================] - 0s 1ms/step
Through careful consideration of all of the prediction-based vs. observation-based contrast visualizations together, I consolidated all of graphics into one singular visualization for you to see below to get a more general perspective of the effectiveness of the Machine Learning model at training and fitting towards predicting Switzerland’s international currency rate with the United States.
```{python}
# Plotting Switzerland's observational (reference) data with the predictions
# of its Machine Learning Model (as a way to visually inspect the effectiveness
# of the model)
plt.plot(dates_switzerland_train, switzerland_train_pred, linewidth=4)
plt.plot(dates_switzerland_train, y_switzerland_train, linewidth=1)
plt.plot(dates_switzerland_val, switzerland_val_pred, linewidth=4)
plt.plot(dates_switzerland_val, y_switzerland_val, linewidth=1)
plt.plot(dates_switzerland_test, switzerland_test_pred, linewidth=4)
plt.plot(dates_switzerland_test, y_switzerland_test, linewidth=1)
plt.legend(["Training Predictions",
"Training Observations",
"Validation Predictions",
"Validation Observations",
"Testing Predictions",
"Testing Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Culmination of the Three Machine Learning Phases of Switzerland's Dataset - Predictions vs. Observations")
plt.show()
```To put it all together, I made one large visualization to encompass all 4 countries’ Machine Learning model prediction-based vs. observation-based visualizations - Austrailia, Canada, the United Kingdom, and Switzerland as shown below.
```{python}
# Plotting all countries' observational (reference) data with the predictions
# of its Machine Learning Model (as a way to visually inspect the effectiveness
# of the model in an overall sense)
plt.plot(dates_austrailia_train, austrailia_train_pred, linewidth=4, linestyle="solid")
plt.plot(dates_austrailia_train, y_austrailia_train, linewidth=1, linestyle="solid")
plt.plot(dates_austrailia_val, austrailia_val_pred, linewidth=4, linestyle="solid")
plt.plot(dates_austrailia_val, y_austrailia_val, linewidth=1, linestyle="solid")
plt.plot(dates_austrailia_test, austrailia_test_pred, linewidth=4, linestyle="solid")
plt.plot(dates_austrailia_test, y_austrailia_test, linewidth=1, linestyle="solid")
plt.plot(dates_canada_train, canada_train_pred, linewidth=4, linestyle="dashed")
plt.plot(dates_canada_train, y_canada_train, linewidth=1, linestyle="dashed")
plt.plot(dates_canada_val, canada_val_pred, linewidth=4, linestyle="dashed")
plt.plot(dates_canada_val, y_canada_val, linewidth=1, linestyle="dashed")
plt.plot(dates_canada_test, canada_test_pred, linewidth=4, linestyle="dashed")
plt.plot(dates_canada_test, y_canada_test, linewidth=1, linestyle="dashed")
plt.plot(dates_united_kingdom_train, united_kingdom_train_pred, linewidth=4, linestyle="dotted")
plt.plot(dates_united_kingdom_train, y_united_kingdom_train, linewidth=1, linestyle="dotted")
plt.plot(dates_united_kingdom_val, united_kingdom_val_pred, linewidth=4, linestyle="dotted")
plt.plot(dates_united_kingdom_val, y_united_kingdom_val, linewidth=1, linestyle="dotted")
plt.plot(dates_united_kingdom_test, united_kingdom_test_pred, linewidth=4, linestyle="dotted")
plt.plot(dates_united_kingdom_test, y_united_kingdom_test, linewidth=1, linestyle="dotted")
plt.plot(dates_switzerland_train, switzerland_train_pred, linewidth=4, linestyle="dashdot")
plt.plot(dates_switzerland_train, y_switzerland_train, linewidth=1, linestyle="dashdot")
plt.plot(dates_switzerland_val, switzerland_val_pred, linewidth=4, linestyle="dashdot")
plt.plot(dates_switzerland_val, y_switzerland_val, linewidth=1, linestyle="dashdot")
plt.plot(dates_switzerland_test, switzerland_test_pred, linewidth=4, linestyle="dashdot")
plt.plot(dates_switzerland_test, y_switzerland_test, linewidth=1, linestyle="dashdot")
plt.legend(["Training Predictions",
"Training Observations",
"Validation Predictions",
"Validation Observations",
"Testing Predictions",
"Testing Observations"])
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Culmination of the Three Machine Learning Phases of All Four Countries' Datasets - Predictions vs. Observations")
plt.show()
```Ultimately, here is the moment of truth: I tried to recursively predict Austrailia’s future expected projection on its international currency rate between the United States through using my LSTM prediction model as shown below. By using the data from the training dataset for Austrailia, I tried to contrast the effectiveness of the model by constrasting its projection to the actual validation and testing data results. However, unfortunately, it did not predict as well as I hoped, but this was a good experiment, nonetheless.
```{python}
# Attempt at using the model to predict into the future for Austrailia's currency
# rate
recursive_pred: list = []
recursive_dates = np.concatenate([dates_austrailia_val, dates_austrailia_test])
for target_date in recursive_dates:
last_window = deepcopy(X_austrailia_train[-1])
next_pred = austrailia_model.predict(np.array([last_window])).flatten()
recursive_pred.append(next_pred)
last_window[-1] = next_pred
```1/1 [==============================] - ETA: 0s1/1 [==============================] - 0s 17ms/step
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To visualize the results of my recursive prediction that I completed, I added these results to the previous large visualization that encompassed all 4 countries’ Machine Learning model prediction-based vs. observation-based visualizations - Austrailia, Canada, the United Kingdom, and Switzerland as shown below.
```{python}
# Plotting all countries' observational (reference) data with the predictions
# of its Machine Learning Model (as a way to visually inspect the effectiveness
# of the model in an overall sense) along with the new recursive prediction
# results
plt.plot(dates_austrailia_train, austrailia_train_pred, linewidth=4, linestyle="solid")
plt.plot(dates_austrailia_train, y_austrailia_train, linewidth=1, linestyle="solid")
plt.plot(dates_austrailia_val, austrailia_val_pred, linewidth=4, linestyle="solid")
plt.plot(dates_austrailia_val, y_austrailia_val, linewidth=1, linestyle="solid")
plt.plot(dates_austrailia_test, austrailia_test_pred, linewidth=4, linestyle="solid")
plt.plot(dates_austrailia_test, y_austrailia_test, linewidth=1, linestyle="solid")
plt.plot(recursive_dates, recursive_pred, linewidth=4, linestyle="solid")
plt.legend(["Training Predictions",
"Training Observations",
"Validation Predictions",
"Validation Observations",
"Testing Predictions",
"Testing Observations",
"Recursive Predictions"], loc="upper right")
plt.rcParams["font.size"] = 8
plt.tight_layout()
plt.xlabel("Historical Date")
plt.ylabel("Currency Rate of the Respective Country to USD")
plt.title("Culmination of the Three Machine Learning Phases of Austrailia's Dataset - Predictions vs. Observations (With Recursive Pred. Attempt)")
plt.show()
```Conclusions
Returning to my attempt to test the ability for my Machine Learning model to predict the International Currency rates for Austrailia from just the range of my training dataset as shown above, I felt that its prediction was acceptable in my opinion giving the averaging across the currency rate values in my validation and testing datasets would have proven to be considerably close in its precision.
Thus, I reached the conclusion that my International Currency Predictor would not be a viable Machine Learning model for any real-life applications. This Machine Learning model raised a valuable point - financial market prediction is a difficult endeavor to accurately predict. From a more general point of view, this International Currency Maching Learning prediction model is not totally inaccurate or untrustworthy but rather it is only on the micro-scale. These financial predictions do not always account for current events in that respective country such as changing domestic or international relations or constantly changing socioeconomic trends which could significantly sway market confidence and impact currency rate fluctuation. Consequently, economists often have to look at larger economic trends across several decades in order to make more educated predictions.
Ultimately, I learned a great deal about the complexities of financial prediction and usage of Machine Learning models as an attempt to solve this issue. Even though my model was not as successful at predicting as I would have hoped, I am interested to see the future of Machine Learning as it soon dominates these economic sub-field and continues to rise in its relevance by being a pivotal talking point for the future and applied soon enough to other sectors of our society.
Reference Sources and Citations (IEEE Format)
To complete this blog post, I used the following online sources as references for developing this:
[1] US International Exchange Rates Dataset:
B. Ferreira, “Foreign Exchange Rates 2000-2019”, 2019. [Online]. Available: https://www.kaggle.com/datasets/brunotly/foreign-exchange-rates-per-dollar-20002019. [Accessed: 04-Sep.-2023].
[2] Tutorial on Basics of LSTM and Prediction & Forecasting in Machine Learning:
Greg Hogg, “Stock Price Prediction & Forecasting with LSTM Neural Networks in Python”, YouTube, 26-Mar.-2022. [Online.] Available: https://www.youtube.com/watch?v=CbTU92pbDKw. [Accessed: 06-Sep.-2023].